Forecast on Water Locking Damage of Low Permeable Reservoir with Quantum Neural Network

Science.gov (United States)

Zhao, Jingyuan; Sun, Yuxue; Feng, Fuping; Zhao, Fulei; Sui, Dianjie; Xu, Jianjun

2018-01-01

It is of great importance in oil-gas reservoir protection to timely and correctly forecast the water locking damage, the greatest damage for low permeable reservoir. An analysis is conducted on the production mechanism and various influence factors of water locking damage, based on which a quantum neuron is constructed based on the information processing manner of a biological neuron and the principle of quantum neural algorithm, besides, the quantum neural network model forecasting the water locking of the reservoir is established and related software is also made to forecast the water locking damage of the gas reservoir. This method has overcome the defects of grey correlation analysis that requires evaluation matrix analysis and complicated operation. According to the practice in Longxi Area of Daqing Oilfield, this method is characterized by fast operation, few system parameters and high accuracy rate (the general incidence rate may reach 90%), which can provide reliable support for the protection technique of low permeable reservoir.

Daily reservoir inflow forecasting combining QPF into ANNs model

Science.gov (United States)

Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

2009-01-01

Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

Daily Reservoir Inflow Forecasting using Deep Learning with Downscaled Multi-General Circulation Models (GCMs) Platform

Science.gov (United States)

Li, D.; Fang, N. Z.

2017-12-01

Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.

Multi-data reservoir history matching for enhanced reservoir forecasting and uncertainty quantification

KAUST Repository

Katterbauer, Klemens

2015-04-01

Reservoir simulations and history matching are critical for fine-tuning reservoir production strategies, improving understanding of the subsurface formation, and forecasting remaining reserves. Production data have long been incorporated for adjusting reservoir parameters. However, the sparse spatial sampling of this data set has posed a significant challenge for efficiently reducing uncertainty of reservoir parameters. Seismic, electromagnetic, gravity and InSAR techniques have found widespread applications in enhancing exploration for oil and gas and monitoring reservoirs. These data have however been interpreted and analyzed mostly separately, rarely exploiting the synergy effects that could result from combining them. We present a multi-data ensemble Kalman filter-based history matching framework for the simultaneous incorporation of various reservoir data such as seismic, electromagnetics, gravimetry and InSAR for best possible characterization of the reservoir formation. We apply an ensemble-based sensitivity method to evaluate the impact of each observation on the estimated reservoir parameters. Numerical experiments for different test cases demonstrate considerable matching enhancements when integrating all data sets in the history matching process. Results from the sensitivity analysis further suggest that electromagnetic data exhibit the strongest impact on the matching enhancements due to their strong differentiation between water fronts and hydrocarbons in the test cases.

Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

DEFF Research Database (Denmark)

Wang, Y.; Chen, H.; Rosbjerg, Dan

2013-01-01

In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which...... is developed by the Japan Meteorological Agency, was used to forecast rainfall with 5 days lead-time in the upper region of the Three Gorges Reservoir (TGR). A conceptual hydrological model, the Xinanjiang Model, has been set up to forecast the inflow flood of TGR by the Ministry of Water Resources Information...... season 2012 as example, real-time dynamic control of the FLWL was implemented by using the forecasted reservoir flood inflow as input. The forecasted inflow with 5 days lead-time rainfall forecast was evaluated by several performance indices, including the mean relative error of the volumetric reservoir...

Surrogate reservoir models for CSI well probabilistic production forecast

Directory of Open Access Journals (Sweden)

Saúl Buitrago

2017-09-01

Full Text Available The aim of this work is to present the construction and use of Surrogate Reservoir Models capable of accurately predicting cumulative oil production for every well stimulated with cyclic steam injection at any given time in a heavy oil reservoir in Mexico considering uncertain variables. The central composite experimental design technique was selected to capture the maximum amount of information from the model response with a minimum number of reservoir models simulations. Four input uncertain variables (the dead oil viscosity with temperature, the reservoir pressure, the reservoir permeability and oil sand thickness hydraulically connected to the well were selected as the ones with more impact on the initial hot oil production rate according to an analytical production prediction model. Twenty five runs were designed and performed with the STARS simulator for each well type on the reservoir model. The results show that the use of Surrogate Reservoir Models is a fast viable alternative to perform probabilistic production forecasting of the reservoir.

A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

Science.gov (United States)

Liu, P.

2013-12-01

Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

Nambe Pueblo Water Budget and Forecasting model.

Energy Technology Data Exchange (ETDEWEB)

Brainard, James Robert

2009-10-01

This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

Indian Academy of Sciences (India)

Seasonal autoregressive integrated moving average (SARIMA) models have been frequently ... studied the perfor- mance of stochastic models against ANN models in ..... the model parameters and Se is the standard error. 2.1.3 Nonlinear term ...... ison of regression, ARIMA and ANN models for reservoir inflow forecasting ...

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

Science.gov (United States)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

Hybrid Stochastic Forecasting Model for Management of Large Open Water Reservoir with Storage Function

Science.gov (United States)

Kozel, Tomas; Stary, Milos

2017-12-01

The main advantage of stochastic forecasting is fan of possible value whose deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. Discharge in measurement profile could be categorized as random process. Content of article is construction and application of forecasting model for managed large open water reservoir with supply function. Model is based on neural networks (NS) and zone models, which forecasting values of average monthly flow from inputs values of average monthly flow, learned neural network and random numbers. Part of data was sorted to one moving zone. The zone is created around last measurement average monthly flow. Matrix of correlation was assembled only from data belonging to zone. The model was compiled for forecast of 1 to 12 month with using backward month flows (NS inputs) from 2 to 11 months for model construction. Data was got ridded of asymmetry with help of Box-Cox rule (Box, Cox, 1964), value r was found by optimization. In next step were data transform to standard normal distribution. The data were with monthly step and forecast is not recurring. 90 years long real flow series was used for compile of the model. First 75 years were used for calibration of model (matrix input-output relationship), last 15 years were used only for validation. Outputs of model were compared with real flow series. For comparison between real flow series (100% successfully of forecast) and forecasts, was used application to management of artificially made reservoir. Course of water reservoir management using Genetic algorithm (GE) + real flow series was compared with Fuzzy model (Fuzzy) + forecast made by Moving zone model. During evaluation process was founding the best size of zone. Results show that the highest number of input did not give the best results and ideal size of zone is in interval from 25 to 35, when course of management was almost same for

Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

Science.gov (United States)

Yi, J.; Choi, C.

2014-12-01

Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

Science.gov (United States)

Gelfan, Alexander; Moreydo, Vsevolod; Motovilov, Yury; Solomatine, Dimitri P.

2018-04-01

A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April-June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

Directory of Open Access Journals (Sweden)

A. Gelfan

2018-04-01

Full Text Available A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia, is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast, and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast. We have studied the following: (1 whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2 whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form outperform the operational forecasts of the April–June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

Application of the Fokker-Plank-Kolmogorov equation for affluence forecast to hydropower reservoirs (Betania Case)

International Nuclear Information System (INIS)

Dominguez Calle, Efrain Antonio

2004-01-01

This paper shows a modeling technique to forecast probability density curves for the flows that represent the monthly affluence to hydropower reservoirs. Briefly, the factors that require affluence forecast in terms of probabilities, the ranges of existing forecast methods as well as the contradiction between those techniques and the real requirements of decision-making procedures are pointed out. The mentioned contradiction is resolved applying the Fokker-Planck-Kolmogorov equation that describes the time evolution of a stochastic process that can be considered as markovian. We show the numerical scheme for this equation, its initial and boundary conditions, and its application results in the case of Betania's reservoir

Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

Science.gov (United States)

Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward

2017-03-01

Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.

Reservoir operation using El Niño forecasts-case study of Daule Peripa and Baba, Ecuador

DEFF Research Database (Denmark)

Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

2014-01-01

Reservoir operation is studied for the Daule Peripa and Baba system in Ecuador, where El Niño events cause anomalously heavy precipitation. Reservoir inflow is modelled by a Markov-switching model using El Niño-Southern Oscillation (ENSO) indices as input. Inflow is forecast using 9-month lead time...... Reservoir. Optimized operation is compared to historical management of Daule Peripa. Hypothetical management scenarios are used as the benchmark for the planned system, for which no operation policy is known. Upper bounds for operational performance are found via dynamic programming by assuming perfect...... knowledge of future inflow. The results highlight the advantages of combining inflow forecasts and storage targets in reservoir operation. © 2014 © 2014 IAHS Press....

Influence of environmental factors on mercury release in hydroelectric reservoirs

Energy Technology Data Exchange (ETDEWEB)

Morrison, K.; Therien, N.

1991-04-01

Due to increased mercury concentrations in fish in hydro-electric reservoirs after flooding, a study was carried out to evaluate the release and transformation of mercury due to vegetation and soil flooded as a result of reservoir creation. Samples of vegetation and soils were immersed in water and concentrations of total mercury, methylmercury and nutrients were followed. The effects of anoxia, pH and temperature on release and transformation were examined. An existing dynamic model of decomposition of flooded materials in reservoirs was modified to include mercury release and transformation, and was calibrated to the experimental data. Amounts of mercury released by the different substrates was of the same order of magnitude. Tree species contributed to the greatest amounts of methylmercury per unit biomass, but the biomass used for these was twigs and foliage. Soil released significant amounts of mercury, but methylation was very low. The model was able to fit well for all substrates except lichen. The model can be adapted to proposed reservoirs to predict nutrient and mecury release and transformation. 175 refs., 38 figs., 38 tabs.

Reservoir water level forecasting using group method of data handling

Science.gov (United States)

Zaji, Amir Hossein; Bonakdari, Hossein; Gharabaghi, Bahram

2018-06-01

Accurately forecasted reservoir water level is among the most vital data for efficient reservoir structure design and management. In this study, the group method of data handling is combined with the minimum description length method to develop a very practical and functional model for predicting reservoir water levels. The models' performance is evaluated using two groups of input combinations based on recent days and recent weeks. Four different input combinations are considered in total. The data collected from Chahnimeh#1 Reservoir in eastern Iran are used for model training and validation. To assess the models' applicability in practical situations, the models are made to predict a non-observed dataset for the nearby Chahnimeh#4 Reservoir. According to the results, input combinations (L, L -1) and (L, L -1, L -12) for recent days with root-mean-squared error (RMSE) of 0.3478 and 0.3767, respectively, outperform input combinations (L, L -7) and (L, L -7, L -14) for recent weeks with RMSE of 0.3866 and 0.4378, respectively, with the dataset from https://www.typingclub.com/st. Accordingly, (L, L -1) is selected as the best input combination for making 7-day ahead predictions of reservoir water levels.

Reservoir Management using seasonal forecasts in Lake Kariba and Lake Kahora Bassa: Initial results and plans

CSIR Research Space (South Africa)

Muchuru, S

2012-06-01

Full Text Available Seasonal forecasting as a tool to improve on reservoir management in Zimbabwe is presented. The focus of the talk is on predicting rainfall extremes over the Lake Kariba catchments. The forecast systems to do the predictions and the levels of skill...

Production forecasting and economic evaluation of horizontal wells completed in natural fractured reservoirs

International Nuclear Information System (INIS)

Evans, R. D.

1996-01-01

A technique for optimizing recovery of hydrocarbons from naturally fractured reservoirs using horizontal well technology was proposed. The technique combines inflow performance analysis, production forecasting and economic considerations, and is based on material balance analysis and linear approximations of reservoir fluid properties as functions of reservoir pressure. An economic evaluation model accounting for the time value of cash flow, interest and inflation rates, is part of the package. Examples of using the technique have been demonstrated. The method is also applied to a gas well producing from a horizontal wellbore intersecting discrete natural fractures. 11 refs., 2 tabs,. 10 figs

Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.

Science.gov (United States)

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2014-07-01

Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Real-Time Flood Control by Tree-Based Model Predictive Control Including Forecast Uncertainty: A Case Study Reservoir in Turkey

Directory of Open Access Journals (Sweden)

Gökçen Uysal

2018-03-01

Full Text Available Optimal control of reservoirs is a challenging task due to conflicting objectives, complex system structure, and uncertainties in the system. Real time control decisions suffer from streamflow forecast uncertainty. This study aims to use Probabilistic Streamflow Forecasts (PSFs having a lead-time up to 48 h as input for the recurrent reservoir operation problem. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC. Deterministic Streamflow Forecasts (DSFs are provided by applying random perturbations on perfect data. PSFs are synthetically generated from DSFs by a new approach which explicitly presents dynamic uncertainty evolution. We assessed different variables in the generation of stochasticity and compared the results using different scenarios. The developed real-time hourly flood control was applied to a test case which had limited reservoir storage and restricted downstream condition. According to hindcasting closed-loop experiment results, TB-MPC outperforms the deterministic counterpart in terms of decreased downstream flood risk according to different independent forecast scenarios. TB-MPC was also tested considering different number of tree branches, forecast horizons, and different inflow conditions. We conclude that using synthetic PSFs in TB-MPC can provide more robust solutions against forecast uncertainty by resolution of uncertainty in trees.

Reservoir release patterns for hydropower operations at the Aspinall Unit on the Gunnison River, Colorado

International Nuclear Information System (INIS)

Yin, S.C.L.; Sedlacek, J.

1995-05-01

This report presents the development of reservoir release patterns for the Aspinall Unit, which includes Blue Mesa, Morrow Point, and Crystal Reservoirs on the Gunnison River in Colorado. Release patterns were assessed for two hydropower operational scenarios--seasonally adjusted steady flows and seasonally adjusted high fluctuating flows--and three representative hydrologic years--moderate (1987), dry (1989), and wet (1983). The release patterns for the operational scenarios were developed with the aid of monthly, daily, and hourly reservoir operational models, which simulate the linked operation of the three Aspinall Unit reservoirs. Also presented are reservoir fluctuations and downstream water surface elevations corresponding to the reservoir release patterns. Both of the hydropower operational scenarios evaluated are based on the ecological research flows proposed by the US Fish and Wildlife Service for the Aspinall Unit. The first operational scenario allows only seasonally adjusted steady flows (no hourly fluctuations at any dam within one day), whereas the second scenario permits high fluctuating flows from Blue Mesa and Morrow Point Reservoirs during certain times of the year. Crystal Reservoir would release a steady flow within each day under both operational scenarios

A Forecasting Approach Combining Self-Organizing Map with Support Vector Regression for Reservoir Inflow during Typhoon Periods

Directory of Open Access Journals (Sweden)

Gwo-Fong Lin

2016-01-01

Full Text Available This study describes the development of a reservoir inflow forecasting model for typhoon events to improve short lead-time flood forecasting performance. To strengthen the forecasting ability of the original support vector machines (SVMs model, the self-organizing map (SOM is adopted to group inputs into different clusters in advance of the proposed SOM-SVM model. Two different input methods are proposed for the SVM-based forecasting method, namely, SOM-SVM1 and SOM-SVM2. The methods are applied to an actual reservoir watershed to determine the 1 to 3 h ahead inflow forecasts. For 1, 2, and 3 h ahead forecasts, improvements in mean coefficient of efficiency (MCE due to the clusters obtained from SOM-SVM1 are 21.5%, 18.5%, and 23.0%, respectively. Furthermore, improvement in MCE for SOM-SVM2 is 20.9%, 21.2%, and 35.4%, respectively. Another SOM-SVM2 model increases the SOM-SVM1 model for 1, 2, and 3 h ahead forecasts obtained improvement increases of 0.33%, 2.25%, and 10.08%, respectively. These results show that the performance of the proposed model can provide improved forecasts of hourly inflow, especially in the proposed SOM-SVM2 model. In conclusion, the proposed model, which considers limit and higher related inputs instead of all inputs, can generate better forecasts in different clusters than are generated from the SOM process. The SOM-SVM2 model is recommended as an alternative to the original SVR (Support Vector Regression model because of its accuracy and robustness.

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

Science.gov (United States)

Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region

Science.gov (United States)

Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Mohd, Nuruol Syuhadaa; Deo, Ravinesh C.; El-Shafie, Ahmed

2017-10-01

Existing forecast models applied for reservoir inflow forecasting encounter several drawbacks, due to the difficulty of the underlying mathematical procedures being to cope with and to mimic the naturalization and stochasticity of the inflow data patterns. In this study, appropriate adjustments to the conventional coactive neuro-fuzzy inference system (CANFIS) method are proposed to improve the mathematical procedure, thus enabling a better detection of the high nonlinearity patterns found in the reservoir inflow training data. This modification includes the updating of the back propagation algorithm, leading to a consequent update of the membership rules and the induction of the centre-weighted set rather than the global weighted set used in feature extraction. The modification also aids in constructing an integrated model that is able to not only detect the nonlinearity in the training data but also the wide range of features within the training data records used to simulate the forecasting model. To demonstrate the model's efficacy, the proposed CANFIS method has been applied to forecast monthly inflow data at Aswan High Dam (AHD), located in southern Egypt. Comparative analyses of the forecasting skill of the modified CANFIS and the conventional ANFIS model are carried out with statistical score indicators to assess the reliability of the developed method. The statistical metrics support the better performance of the developed CANFIS model, which significantly outperforms the ANFIS model to attain a low relative error value (23%), mean absolute error (1.4 BCM month-1), root mean square error (1.14 BCM month-1), and a relative large coefficient of determination (0.94). The present study ascertains the better utility of the modified CANFIS model in respect to the traditional ANFIS model applied in reservoir inflow forecasting for a semi-arid region.

EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

KAUST Repository

Katterbauer, Klemens

2014-10-01

New developments of electromagnetic and seismic techniques have recently revolutionized the oil and gas industry. Time-lapse seismic data is providing engineers with tools to more accurately track the dynamics of multi-phase reservoir fluid flows. With the challenges faced in distinguishing between hydrocarbons and water via seismic methods, the industry has been looking at electromagnetic techniques in order to exploit the strong contrast in conductivity between hydrocarbons and water. Incorporating this information into reservoir simulation is expected to considerably enhance the forecasting of the reservoir, hence optimizing production and reducing costs. Conventional approaches typically invert the seismic and electromagnetic data in order to transform them into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential artifacts. Here we introduce a new approach to incorporate seismic and electromagnetic data attributes directly into the history matching process. To avoid solving inverse problems and exploit information in the dynamics of the flow, we exploit petrophysical transformations to simultaneously incorporate time lapse seismic and electromagnetic data attributes using different ensemble Kalman-based history matching techniques. Our simulation results show enhanced predictability of the critical reservoir parameters and reduce uncertainties in model simulations, outperforming with only production data or the inclusion of either seismic or electromagnetic data. A statistical test is performed to confirm the significance of the results. © 2014 Elsevier B.V. All rights reserved.

Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

Science.gov (United States)

Turner, Sean; Galelli, Stefano; Wilcox, Karen

2015-04-01

Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating

A statistical data assimilation method for seasonal streamflow forecasting to optimize hydropower reservoir management in data-scarce regions

Science.gov (United States)

Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.

2017-12-01

Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was

Accuracy Enhancement for Forecasting Water Levels of Reservoirs and River Streams Using a Multiple-Input-Pattern Fuzzification Approach

Directory of Open Access Journals (Sweden)

Nariman Valizadeh

2014-01-01

Full Text Available Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influencing the forecasting procedure. The artificial neurofuzzy interface system (ANFIS is one of the most accurate models used in water resource management. Because the membership functions (MFs possess the characteristics of smoothness and mathematical components, each set of input data is able to yield the best result using a certain type of MF in the ANFIS models. The objective of this study is to define the different ANFIS model by applying different types of MFs for each type of input to forecast the water level in two case studies, the Klang Gates Dam and Rantau Panjang station on the Johor river in Malaysia, to compare the traditional ANFIS model with the new introduced one in two different situations, reservoir and stream, showing the new approach outweigh rather than the traditional one in both case studies. This objective is accomplished by evaluating the model fitness and performance in daily forecasting.

Accuracy enhancement for forecasting water levels of reservoirs and river streams using a multiple-input-pattern fuzzification approach.

Science.gov (United States)

Valizadeh, Nariman; El-Shafie, Ahmed; Mirzaei, Majid; Galavi, Hadi; Mukhlisin, Muhammad; Jaafar, Othman

2014-01-01

Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influencing the forecasting procedure. The artificial neurofuzzy interface system (ANFIS) is one of the most accurate models used in water resource management. Because the membership functions (MFs) possess the characteristics of smoothness and mathematical components, each set of input data is able to yield the best result using a certain type of MF in the ANFIS models. The objective of this study is to define the different ANFIS model by applying different types of MFs for each type of input to forecast the water level in two case studies, the Klang Gates Dam and Rantau Panjang station on the Johor river in Malaysia, to compare the traditional ANFIS model with the new introduced one in two different situations, reservoir and stream, showing the new approach outweigh rather than the traditional one in both case studies. This objective is accomplished by evaluating the model fitness and performance in daily forecasting.

Ensemble hydrological forecast efficiency evolution over various issue dates and lead-time: case study for the Cheboksary reservoir (Volga River)

Science.gov (United States)

Gelfan, Alexander; Moreido, Vsevolod

2017-04-01

Ensemble hydrological forecasting allows for describing uncertainty caused by variability of meteorological conditions in the river basin for the forecast lead-time. At the same time, in snowmelt-dependent river basins another significant source of uncertainty relates to variability of initial conditions of the basin (snow water equivalent, soil moisture content, etc.) prior to forecast issue. Accurate long-term hydrological forecast is most crucial for large water management systems, such as the Cheboksary reservoir (the catchment area is 374 000 sq.km) located in the Middle Volga river in Russia. Accurate forecasts of water inflow volume, maximum discharge and other flow characteristics are of great value for this basin, especially before the beginning of the spring freshet season that lasts here from April to June. The semi-distributed hydrological model ECOMAG was used to develop long-term ensemble forecast of daily water inflow into the Cheboksary reservoir. To describe variability of the meteorological conditions and construct ensemble of possible weather scenarios for the lead-time of the forecast, two approaches were applied. The first one utilizes 50 weather scenarios observed in the previous years (similar to the ensemble streamflow prediction (ESP) procedure), the second one uses 1000 synthetic scenarios simulated by a stochastic weather generator. We investigated the evolution of forecast uncertainty reduction, expressed as forecast efficiency, over various consequent forecast issue dates and lead time. We analyzed the Nash-Sutcliffe efficiency of inflow hindcasts for the period 1982 to 2016 starting from 1st of March with 15 days frequency for lead-time of 1 to 6 months. This resulted in the forecast efficiency matrix with issue dates versus lead-time that allows for predictability identification of the basin. The matrix was constructed separately for observed and synthetic weather ensembles.

Effects of the uncertainty of energy price and water availability forecasts on the operation of Alpine hydropower reservoir systems

Science.gov (United States)

Anghileri, D.; Castelletti, A.; Burlando, P.

2016-12-01

European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow

Dynamic Management of Releases for the Delaware River Basin using NYC's Operations Support Tool

Science.gov (United States)

Weiss, W.; Wang, L.; Murphy, T.; Muralidhar, D.; Tarrier, B.

2011-12-01

The New York City Department of Environmental Protection (DEP) has initiated design of an Operations Support Tool (OST), a state-of-the-art decision support system to provide computational and predictive support for water supply operations and planning. Using an interim version of OST, DEP and the New York State Department of Environmental Conservation (DEC) have developed a provisional, one-year Delaware River Basin reservoir release program to succeed the existing Flexible Flow Management Program (FFMP) which expired on May 31, 2011. The FFMP grew out of the Good Faith Agreement of 1983 among the four Basin states (New York, New Jersey, Pennsylvania, and Delaware) that established modified diversions and flow targets during drought conditions. It provided a set of release schedules as a framework for managing diversions and releases from New York City's Delaware Basin reservoirs in order to support multiple objectives, including water supply, drought mitigation, flood mitigation, tailwaters fisheries, main stem habitat, recreation, and salinity repulsion. The provisional program (OST-FFMP) defines available water based on current Upper Delaware reservoir conditions and probabilistic forecasts of reservoir inflow. Releases are then set based on a set of release schedules keyed to the water availability. Additionally, OST-FFMP attempts to provide enhanced downstream flood protection by making spill mitigation releases to keep the Delaware System reservoirs at a seasonally varying conditional storage objective. The OST-FFMP approach represents a more robust way of managing downstream releases, accounting for predicted future hydrologic conditions by making more water available for release when conditions are forecasted to be wet and protecting water supply reliability when conditions are forecasted to be dry. Further, the dynamic nature of the program allows the release decision to be adjusted as hydrologic conditions change. OST simulations predict that this

Wind field forecast for accidental release of radiative materials

International Nuclear Information System (INIS)

Kang Ling; Chen Jiayi; Cai Xuhui

2003-01-01

A meso-scale wind field forecast model was designed for emergency environmental assessment in case of accidental release of radiative materials from a nuclear power station. Actual practice of the model showed that it runs fast, has wind field prediction function, and the result given is accurate. With meteorological data collected from weather stations, and pre-treated by a wind field diagnostic model, the initial wind fields at different times were inputted as initial values and assimilation fields for the forecasting model. The model, in turn, worked out to forecast meso-scale wind field of 24 hours in a horizontal domain of 205 km x 205 km. And then, the diagnostic model was employed again with the forecasting data to obtain more detail information of disturbed wind field by local terrain in a smaller domain of 20.5 km x 20.5 km, of which the nuclear power station is at the center. Using observation data in January, April, July and October of 1996 over the area of Hangzhou Bay, wind fields in these 4 months were simulated by different assimilation time and number of the weather stations for a sensitive test. Results indicated that the method used here has increased accuracy of the forecasted wind fields. And incorporating diagnostic method with the wind field forecast model has greatly increased efficiency of the wind field forecast for the smaller domain. This model and scheme have been used in Environmental Consequence Assessment System of Nuclear Accident in Qinshan Area

Using a Bayesian Probabilistic Forecasting Model to Analyze the Uncertainty in Real-Time Dynamic Control of the Flood Limiting Water Level for Reservoir Operation

DEFF Research Database (Denmark)

Liu, Dedi; Li, Xiang; Guo, Shenglian

2015-01-01

Dynamic control of the flood limiting water level (FLWL) is a valuable and effective way to maximize the benefits from reservoir operation without exceeding the design risk. In order to analyze the impacts of input uncertainty, a Bayesian forecasting system (BFS) is adopted. Applying quantile water...... inflow values and their uncertainties obtained from the BFS, the reservoir operation results from different schemes can be analyzed in terms of benefits, dam safety, and downstream impacts during the flood season. When the reservoir FLWL dynamic control operation is implemented, there are two fundamental......, also deterministic water inflow was tested. The proposed model in the paper emphasizes the importance of analyzing the uncertainties of the water inflow forecasting system for real-time dynamic control of the FLWL for reservoir operation. For the case study, the selected quantile inflow from...

Climate variability and sedimentation of a hydropower reservoir

International Nuclear Information System (INIS)

Riedel, M.

2008-01-01

As part of the relicensing of a large Hydroelectric Project in the central Appalachians, large scale watershed and reservoir sedimentation models were developed to forecast potential sedimentation scenarios. The GIS based watershed model was spatially explicit and calibrated to long term observed data. Potential socio/economic development scenarios were used to construct future watershed land cover scenarios. Climatic variability and potential change analysis were used to identify future climate regimes and shifts in precipitation and temperature patterns. Permutations of these development and climate changes were forecasted over 50 years and used to develop sediment yield regimes to the project reservoir. Extensive field work and reservoir survey, including current and wave instrumentation, were used to characterize the project watershed, rivers and reservoir hydrodynamics. A fully 3 dimensional hydrodynamic reservoir sedimentation model was developed for the project and calibrated to observed data. Hydrologic and sedimentation results from watershed forecasting provided boundary conditions for reservoir inputs. The calibrated reservoir model was then used to forecast changes in reservoir sedimentation and storage capacity under different future climate scenarios. Results indicated unique zones of advancing sediment deltas and temporary storage areas. Forecasted changes in reservoir bathymetry and sedimentation patterns were also developed for the various climate change scenarios. The warmer and wetter scenario produced sedimentation impacts similar to extensive development under no climate change. The results of these analyses are being used to develop collaborative watershed and soil conservation partnerships to reduce future soil losses and reservoir sedimentation from projected development. (author)

Effect of heterogeneity in a horizontal well with multiple fractures on the long term forecast in shale gas reservoirs

Energy Technology Data Exchange (ETDEWEB)

Nobakht, M.; Ambrose, R.; Clarkson, C.R. [Society of Petroleum Engineers (Canada)

2011-07-01

Multiple fracture horizontal wells (MFHWs) are the most popular type of method used for exploiting shale gas reservoirs. When analyzing MFHW's a homogeneous completion model is often used, but this rarely occurs in the field. This paper develops a hybrid method for forecasting MFHWs based on a heterogeneous completion and investigates the effect of completion heterogeneity on production forecasts. First, a current forecasting method for homogeneous completions was modified for heterogeneous completions. The new forecasting method was then validated using a numerical simulation. A relationship between Arps' hyperbolic decline exponent and the heterogeneity of a completion for a particular case was then developed. Lastly, a field case was analyzed to compare the impact of forecasting with and without taking a heterogeneous completion into consideration. Through analysis and simulations this paper found that the long-term forecast of MFHWs can be greatly impacted should heterogeneity of the completion be ignored.

Designing adaptive operating rules for a large multi-purpose reservoir

Science.gov (United States)

Geressu, Robel; Rougé, Charles; Harou, Julien

2017-04-01

Reservoirs whose live storage capacity is large compared with annual inflow have "memory", i.e., their storage levels contain information about past inflows and reservoir operations. Such "long-memory" reservoirs can be found in basins in dry regions such as the Nile River Basin in Africa, the Colorado River Basin in the US, or river basins in Western and Central Asia. There the effects of a dry year have the potential to impact reservoir levels and downstream releases for several subsequent years, prompting tensions in transboundary basins. Yet, current reservoir operation rules in those reservoirs do not reflect this by integrating past climate history and release decisions among the factors that influence operating decisions. This work proposes and demonstrates an adaptive reservoir operating rule that explicitly accounts for the recent history of release decisions, and not only current storage level and near-term inflow forecasts. This implies adding long-term (e.g., multiyear) objectives to the existing short-term (e.g., annual) ones. We apply these operating rules to the Grand Ethiopian Renaissance Dam, a large reservoir under construction on the Blue Nile River. Energy generation has to be balanced with the imperative of releasing enough water in low flow years (e.g., the minimum 1, 2 or 3 year cumulative flow) to avoid tensions with downstream countries, Sudan and Egypt. Maximizing the minimum multi-year releases could be of interest for the Nile problem to minimize the impact on performance of the large High Aswan Dam in Egypt. Objectives include maximizing the average and minimum annual energy generation and maximizing the minimum annual, two year and three year cumulative releases. The system model is tested using 30 stochastically generated streamflow series. One can then derive adaptive release rules depending on the value of one- and two-year total releases with respect to thresholds. Then, there are 3 sets of release rules for the reservoir depending

Sparse Bayesian learning machine for real-time management of reservoir releases

Science.gov (United States)

Khalil, Abedalrazq; McKee, Mac; Kemblowski, Mariush; Asefa, Tirusew

2005-11-01

Water scarcity and uncertainties in forecasting future water availabilities present serious problems for basin-scale water management. These problems create a need for intelligent prediction models that learn and adapt to their environment in order to provide water managers with decision-relevant information related to the operation of river systems. This manuscript presents examples of state-of-the-art techniques for forecasting that combine excellent generalization properties and sparse representation within a Bayesian paradigm. The techniques are demonstrated as decision tools to enhance real-time water management. A relevance vector machine, which is a probabilistic model, has been used in an online fashion to provide confident forecasts given knowledge of some state and exogenous conditions. In practical applications, online algorithms should recognize changes in the input space and account for drift in system behavior. Support vectors machines lend themselves particularly well to the detection of drift and hence to the initiation of adaptation in response to a recognized shift in system structure. The resulting model will normally have a structure and parameterization that suits the information content of the available data. The utility and practicality of this proposed approach have been demonstrated with an application in a real case study involving real-time operation of a reservoir in a river basin in southern Utah.

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

Science.gov (United States)

Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

2011-12-01

HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of

Sampling from stochastic reservoir models constrained by production data

Energy Technology Data Exchange (ETDEWEB)

Hegstad, Bjoern Kaare

1997-12-31

When a petroleum reservoir is evaluated, it is important to forecast future production of oil and gas and to assess forecast uncertainty. This is done by defining a stochastic model for the reservoir characteristics, generating realizations from this model and applying a fluid flow simulator to the realizations. The reservoir characteristics define the geometry of the reservoir, initial saturation, petrophysical properties etc. This thesis discusses how to generate realizations constrained by production data, that is to say, the realizations should reproduce the observed production history of the petroleum reservoir within the uncertainty of these data. The topics discussed are: (1) Theoretical framework, (2) History matching, forecasting and forecasting uncertainty, (3) A three-dimensional test case, (4) Modelling transmissibility multipliers by Markov random fields, (5) Up scaling, (6) The link between model parameters, well observations and production history in a simple test case, (7) Sampling the posterior using optimization in a hierarchical model, (8) A comparison of Rejection Sampling and Metropolis-Hastings algorithm, (9) Stochastic simulation and conditioning by annealing in reservoir description, and (10) Uncertainty assessment in history matching and forecasting. 139 refs., 85 figs., 1 tab.

Improving reservoir history matching of EM heated heavy oil reservoirs via cross-well seismic tomography

KAUST Repository

Katterbauer, Klemens

2014-01-01

Enhanced recovery methods have become significant in the industry\\'s drive to increase recovery rates from oil and gas reservoirs. For heavy oil reservoirs, the immobility of the oil at reservoir temperatures, caused by its high viscosity, limits the recovery rates and strains the economic viability of these fields. While thermal recovery methods, such as steam injection or THAI, have extensively been applied in the field, their success has so far been limited due to prohibitive heat losses and the difficulty in controlling the combustion process. Electromagnetic (EM) heating via high-frequency EM radiation has attracted attention due to its wide applicability in different environments, its efficiency, and the improved controllability of the heating process. While becoming a promising technology for heavy oil recovery, its effect on overall reservoir production and fluid displacements are poorly understood. Reservoir history matching has become a vital tool for the oil & gas industry to increase recovery rates. Limited research has been undertaken so far to capture the nonlinear reservoir dynamics and significantly varying flow rates for thermally heated heavy oil reservoir that may notably change production rates and render conventional history matching frameworks more challenging. We present a new history matching framework for EM heated heavy oil reservoirs incorporating cross-well seismic imaging. Interfacing an EM heating solver to a reservoir simulator via Andrade’s equation, we couple the system to an ensemble Kalman filter based history matching framework incorporating a cross-well seismic survey module. With increasing power levels and heating applied to the heavy oil reservoirs, reservoir dynamics change considerably and may lead to widely differing production forecasts and increased uncertainty. We have shown that the incorporation of seismic observations into the EnKF framework can significantly enhance reservoir simulations, decrease forecasting

A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

KAUST Repository

Katterbauer, Klemens; Hoteit, Ibrahim; Sun, Shuyu

2014-01-01

production forecasts and optimizing reservoir exploitation. Reservoir history matching has played here a key role incorporating production, seismic, electromagnetic and logging data for forecasting the development of reservoirs and its depletion

Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

Science.gov (United States)

Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

2016-04-01

Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of

Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Chun-tian Cheng

2015-07-01

Full Text Available Accurate daily runoff forecasting is of great significance for the operation control of hydropower station and power grid. Conventional methods including rainfall-runoff models and statistical techniques usually rely on a number of assumptions, leading to some deviation from the exact results. Artificial neural network (ANN has the advantages of high fault-tolerance, strong nonlinear mapping and learning ability, which provides an effective method for the daily runoff forecasting. However, its training has certain drawbacks such as time-consuming, slow learning speed and easily falling into local optimum, which cannot be ignored in the real world application. In order to overcome the disadvantages of ANN model, the artificial neural network model based on quantum-behaved particle swarm optimization (QPSO, ANN-QPSO for short, is presented for the daily runoff forecasting in this paper, where QPSO was employed to select the synaptic weights and thresholds of ANN, while ANN was used for the prediction. The proposed model can combine the advantages of both QPSO and ANN to enhance the generalization performance of the forecasting model. The methodology is assessed by using the daily runoff data of Hongjiadu reservoir in southeast Guizhou province of China from 2006 to 2014. The results demonstrate that the proposed approach achieves much better forecast accuracy than the basic ANN model, and the QPSO algorithm is an alternative training technique for the ANN parameters selection.

The FAST-T approach for operational, real time, short term hydrological forecasting: Results from the Betania Hydropower Reservoir case study

Science.gov (United States)

Domínguez, Efraín; Angarita, Hector; Rosmann, Thomas; Mendez, Zulma; Angulo, Gustavo

2013-04-01

A viable quantitative hydrological forecasting service is a combination of technological elements, personnel and knowledge, working together to establish a stable operational cycle of forecasts emission, dissemination and assimilation; hence, the process for establishing such system usually requires significant resources and time to reach an adequate development and integration in order to produce forecasts with acceptable levels of performance. Here are presented the results of this process for the recently implemented Operational Forecast Service for the Betania's Hydropower Reservoir - or SPHEB, located at the Upper-Magdalena River Basin (Colombia). The current scope of the SPHEB includes forecasting of water levels and discharge for the three main streams affluent to the reservoir, for lead times between +1 to +57 hours, and +1 to +10 days. The core of the SPHEB is the Flexible, Adaptive, Simple and Transient Time forecasting approach, namely FAST-T. This comprises of a set of data structures, mathematical kernel, distributed computing and network infrastructure designed to provide seamless real-time operational forecast and automatic model adjustment in case of failures in data transmission or assimilation. Among FAST-T main features are: an autonomous evaluation and detection of the most relevant information for the later configuration of forecasting models; an adaptively linearized mathematical kernel, the optimal adaptive linear combination or OALC, which provides a computationally simple and efficient algorithm for real-time applications; and finally, a meta-model catalog, containing prioritized forecast models at given stream conditions. The SPHEB is at present feed by the fraction of hydrological monitoring network installed at the basin that has telemetric capabilities via NOAA-GOES satellites (8 stages, approximately 47%) with data availability of about a 90% at one hour intervals. However, there is a dense network of 'conventional' hydro

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

Integrating a Storage Factor into R-NARX Neural Networks for Flood Forecasts

Science.gov (United States)

Chou, Po-Kai; Chang, Li-Chiu; Chang, Fi-John; Shih, Ban-Jwu

2017-04-01

Because mountainous terrains and steep landforms rapidly accelerate the speed of flood flow in Taiwan island, accurate multi-step-ahead inflow forecasts during typhoon events for providing reliable information benefiting the decision-makings of reservoir pre-storm release and flood-control operation are considered crucial and challenging. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields. This study proposes a recurrent configuration of the nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, with various effective inputs to forecast the inflows of the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, during typhoon periods. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modelling nonlinear dynamical systems. A large number of hourly rainfall and inflow data sets collected from 95 historical typhoon events in the last thirty years are used to train, validate and test the models. The potential input variables, including rainfall in previous time steps (one to six hours), cumulative rainfall, the storage factor and the storage function, are assessed, and various models are constructed with their reliability and accuracy being tested. We find that the previous (t-2) rainfall and cumulative rainfall are crucial inputs and the storage factor and the storage function would also improve the forecast accuracy of the models. We demonstrate that the R-NARX model not only can accurately forecast the inflows but also effectively catch the peak flow without adopting observed inflow data during the entire typhoon period. Besides, the model with the storage factor is superior to the model with the storage function, where its improvement can reach 24%. This approach can well model the rainfall-runoff process for the entire flood forecasting period without the use of observed inflow data and can provide

Reservoir management

International Nuclear Information System (INIS)

Satter, A.; Varnon, J.E.; Hoang, M.T.

1992-01-01

A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neural reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers, geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

Reservoir management

International Nuclear Information System (INIS)

Satter, A.; Varnon, J.E.; Hoang, M.T.

1992-01-01

A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neutral reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

KAUST Repository

Katterbauer, Klemens

2016-08-25

Reservoir history matching is assuming a critical role in understanding reservoir characteristics, tracking water fronts, and forecasting production. While production data have been incorporated for matching reservoir production levels and estimating critical reservoir parameters, the sparse spatial nature of this dataset limits the efficiency of the history matching process. Recently, gravimetry techniques have significantly advanced to the point of providing measurement accuracy in the microgal range and consequently can be used for the tracking of gas displacement caused by water influx. While gravity measurements provide information on subsurface density changes, i.e., the composition of the reservoir, these data do only yield marginal information about temporal displacements of oil and inflowing water. We propose to complement gravimetric data with interferometric synthetic aperture radar surface deformation data to exploit the strong pressure deformation relationship for enhancing fluid flow direction forecasts. We have developed an ensemble Kalman-filter-based history matching framework for gas, gas condensate, and volatile oil reservoirs, which synergizes time-lapse gravity and interferometric synthetic aperture radar data for improved reservoir management and reservoir forecasts. Based on a dual state-parameter estimation algorithm separating the estimation of static reservoir parameters from the dynamic reservoir parameters, our numerical experiments demonstrate that history matching gravity measurements allow monitoring the density changes caused by oil-gas phase transition and water influx to determine the saturation levels, whereas the interferometric synthetic aperture radar measurements help to improve the forecasts of hydrocarbon production and water displacement directions. The reservoir estimates resulting from the dual filtering scheme are on average 20%-40% better than those from the joint estimation scheme, but require about a 30% increase in

Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

KAUST Repository

Katterbauer, Klemens; Arango, Santiago; Sun, Shuyu; Hoteit, Ibrahim

2016-01-01

Reservoir history matching is assuming a critical role in understanding reservoir characteristics, tracking water fronts, and forecasting production. While production data have been incorporated for matching reservoir production levels

A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

KAUST Repository

Katterbauer, Klemens

2014-03-25

The oil & gas industry has been the backbone of the world\\'s economy in the last century and will continue to be in the decades to come. With increasing demand and conventional reservoirs depleting, new oil industry projects have become more complex and expensive, operating in areas that were previously considered impossible and uneconomical. Therefore, good reservoir management is key for the economical success of complex projects requiring the incorporation of reliable uncertainty estimates for reliable production forecasts and optimizing reservoir exploitation. Reservoir history matching has played here a key role incorporating production, seismic, electromagnetic and logging data for forecasting the development of reservoirs and its depletion. With the advances in the last decade, electromagnetic techniques, such as crosswell electromagnetic tomography, have enabled engineers to more precisely map the reservoirs and understand their evolution. Incorporating the large amount of data efficiently and reducing uncertainty in the forecasts has been one of the key challenges for reservoir management. Computing the conductivity distribution for the field for adjusting parameters in the forecasting process via solving the inverse problem has been a challenge, due to the strong ill-posedness of the inversion problem and the extensive manual calibration required, making it impossible to be included into an efficient reservoir history matching forecasting algorithm. In the presented research, we have developed a novel Finite Difference Time Domain (FDTD) based method for incorporating electromagnetic data directly into the reservoir simulator. Based on an extended Archie relationship, EM simulations are performed for both forecasted and Porosity-Saturation retrieved conductivity parameters being incorporated directly into an update step for the reservoir parameters. This novel direct update method has significant advantages such as that it overcomes the expensive and ill

Forecasting of future earthquakes in the northeast region of India considering energy released concept

Science.gov (United States)

Zarola, Amit; Sil, Arjun

2018-04-01

This study presents the forecasting of time and magnitude size of the next earthquake in the northeast India, using four probability distribution models (Gamma, Lognormal, Weibull and Log-logistic) considering updated earthquake catalog of magnitude Mw ≥ 6.0 that occurred from year 1737-2015 in the study area. On the basis of past seismicity of the region, two types of conditional probabilities have been estimated using their best fit model and respective model parameters. The first conditional probability is the probability of seismic energy (e × 1020 ergs), which is expected to release in the future earthquake, exceeding a certain level of seismic energy (E × 1020 ergs). And the second conditional probability is the probability of seismic energy (a × 1020 ergs/year), which is expected to release per year, exceeding a certain level of seismic energy per year (A × 1020 ergs/year). The logarithm likelihood functions (ln L) were also estimated for all four probability distribution models. A higher value of ln L suggests a better model and a lower value shows a worse model. The time of the future earthquake is forecasted by dividing the total seismic energy expected to release in the future earthquake with the total seismic energy expected to release per year. The epicentre of recently occurred 4 January 2016 Manipur earthquake (M 6.7), 13 April 2016 Myanmar earthquake (M 6.9) and the 24 August 2016 Myanmar earthquake (M 6.8) are located in zone Z.12, zone Z.16 and zone Z.15, respectively and that are the identified seismic source zones in the study area which show that the proposed techniques and models yield good forecasting accuracy.

[Sediment-water flux and processes of nutrients and gaseous nitrogen release in a China River Reservoir].

Science.gov (United States)

Chen, Zhu-hong; Chen, Neng-wang; Wu, Yin-qi; Mo, Qiong-li; Zhou, Xing-peng; Lu, Ting; Tian, Yun

2014-09-01

The key processes and fluxes of nutrients (N and P) and gaseous N (N2 and N2O) across the sediment-water interface in a river reservoir (Xipi) of the Jiulong River watershed in southeast China were studied. Intact core sediment incubation of nutrients exchange, in-situ observation and lab incubation of excess dissolved N2 and N2O (products of nitrification, denitrification and Anammox), and determination of physiochemical and microbe parameters were carried out in 2013 for three representative sites along the lacustrine zone of the reservoir. Results showed that ammonium and phosphate were generally released from sediment to overlying water [with averaged fluxes of N (479.8 ± 675.4) mg. (m2. d)-1 and P (4. 56 ± 0.54) mg. (m2 d) -1] , while nitrate and nitrite diffused into the sediment. Flood events in the wet season could introduce a large amount of particulate organic matter that would be trapped by the dam reservoir, resulting in the high release fluxes of ammonium and phosphate observed in the following low-flow season. No clear spatial variation of sediment nutrient release was found in the lacustrine zone of the reservoir. Gaseous N release was dominated by excess dissolved N2 (98% of total), and the N2 flux from sediment was (15.8 ± 12. 5) mg (m2. d) -1. There was a longitudinal and vertical variation of excess dissolved N2, reflecting the combined results of denitrification and Anammox occurring in anoxic sediment and fluvial transport. Nitrification mainly occurred in the lower lacustrine zone, and the enrichment of N2O was likely regulated by the ratio of ammonium to DIN in water.

Multi Data Reservoir History Matching using the Ensemble Kalman Filter

KAUST Repository

Katterbauer, Klemens

2015-05-01

Reservoir history matching is becoming increasingly important with the growing demand for higher quality formation characterization and forecasting and the increased complexity and expenses for modern hydrocarbon exploration projects. History matching has long been dominated by adjusting reservoir parameters based solely on well data whose spatial sparse sampling has been a challenge for characterizing the flow properties in areas away from the wells. Geophysical data are widely collected nowadays for reservoir monitoring purposes, but has not yet been fully integrated into history matching and forecasting fluid flow. In this thesis, I present a pioneering approach towards incorporating different time-lapse geophysical data together for enhancing reservoir history matching and uncertainty quantification. The thesis provides several approaches to efficiently integrate multiple geophysical data, analyze the sensitivity of the history matches to observation noise, and examine the framework’s performance in several settings, such as the Norne field in Norway. The results demonstrate the significant improvements in reservoir forecasting and characterization and the synergy effects encountered between the different geophysical data. In particular, the joint use of electromagnetic and seismic data improves the accuracy of forecasting fluid properties, and the usage of electromagnetic data has led to considerably better estimates of hydrocarbon fluid components. For volatile oil and gas reservoirs the joint integration of gravimetric and InSAR data has shown to be beneficial in detecting the influx of water and thereby improving the recovery rate. Summarizing, this thesis makes an important contribution towards integrated reservoir management and multiphysics integration for reservoir history matching.

Report (summarized) for fiscal 2000 on survey for demonstration of geothermal exploration technologies. Development of exploration method using reservoir bed fluctuation (Theme 5-1. Reservoir fluctuation forecasting technology); 2000 nendo chinetsu tansa gijutsu to kensho chosa hokokusho (yoyaku). Choryuso hendo tansaho kaihatsu - 5-1 (choryuso hendo yosoku gijutsu)

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

With an objective of developing a method effective to evaluate reservoir beds in the initial stage of development, to maintain output stability of power plants after having started the operation and to extract reservoirs existing in the vicinity of areas that have already been developed, R and D has been performed in relation with a reservoir simulator on post processors for gravity, SP, and resistivity, and on reservoir modeling. This paper summarizes the achievements in fiscal 2000. In developing the resistivity post processor, a prototype was completed. In developing the resistivity post processor for MT/CSAMT method, an analysis code was structured, and an input/output format was discussed. In developing the seismic wave post processor, a seismic wave characteristics fluctuation model was formulated. Regarding the input/output aiding GUI tools, a conceptual design was made. In developing the reservoir modeling technology, production forecasting simulation using a porous model and an MINC model was performed for the Sumikawa area. Based on the result thereof, forecast calculation was carried out on gravity change, resistivity change and natural potential change. (NEDO)

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Science.gov (United States)

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

OpenAIRE

Jun-He Yang; Ching-Hsue Cheng; Chia-Pan Chan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting m...

The Adaptive-Clustering and Error-Correction Method for Forecasting Cyanobacteria Blooms in Lakes and Reservoirs

Directory of Open Access Journals (Sweden)

Xiao-zhe Bai

2017-01-01

Full Text Available Globally, cyanobacteria blooms frequently occur, and effective prediction of cyanobacteria blooms in lakes and reservoirs could constitute an essential proactive strategy for water-resource protection. However, cyanobacteria blooms are very complicated because of the internal stochastic nature of the system evolution and the external uncertainty of the observation data. In this study, an adaptive-clustering algorithm is introduced to obtain some typical operating intervals. In addition, the number of nearest neighbors used for modeling was optimized by particle swarm optimization. Finally, a fuzzy linear regression method based on error-correction was used to revise the model dynamically near the operating point. We found that the combined method can characterize the evolutionary track of cyanobacteria blooms in lakes and reservoirs. The model constructed in this paper is compared to other cyanobacteria-bloom forecasting methods (e.g., phase space reconstruction and traditional-clustering linear regression, and, then, the average relative error and average absolute error are used to compare the accuracies of these models. The results suggest that the proposed model is superior. As such, the newly developed approach achieves more precise predictions, which can be used to prevent the further deterioration of the water environment.

Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs

Directory of Open Access Journals (Sweden)

Zhengchao Xie

2012-01-01

Full Text Available Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult to model the growth of algae species. Recently, support vector machine (SVM was reported to have advantages of only requiring a small amount of samples, high degree of prediction accuracy, and long prediction period to solve the nonlinear problems. In this study, the SVM-based prediction and forecast models for phytoplankton abundance in Macau Storage Reservoir (MSR are proposed, in which the water parameters of pH, SiO2, alkalinity, bicarbonate (HCO3 -, dissolved oxygen (DO, total nitrogen (TN, UV254, turbidity, conductivity, nitrate, total nitrogen (TN, orthophosphate (PO4 3−, total phosphorus (TP, suspended solid (SS and total organic carbon (TOC selected from the correlation analysis of the 23 monthly water variables were included, with 8-year (2001–2008 data for training and the most recent 3 years (2009–2011 for testing. The modeling results showed that the prediction and forecast powers were estimated as approximately 0.76 and 0.86, respectively, showing that the SVM is an effective new way that can be used for monitoring algal bloom in drinking water storage reservoir.

Integrated Drought Monitoring and Forecasts for Decision Making in Water and Agricultural Sectors over the Southeastern US under Changing Climate

Science.gov (United States)

Arumugam, S.; Mazrooei, A.; Ward, R.

2017-12-01

Changing climate arising from structured oscillations such as ENSO and rising temperature poses challenging issues in meeting the increasing water demand (due to population growth) for public supply and agriculture over the Southeast US. This together with infrastructural (e.g., most reservoirs being within-year systems) and operational (e.g., static rule curves) constraints requires an integrated approach that seamlessly monitors and forecasts water and soil moisture conditions to support adaptive decision making in water and agricultural sectors. In this talk, we discuss the utility of an integrated drought management portal that both monitors and forecasts streamflow and soil moisture over the southeast US. The forecasts are continuously developed and updated by forcing monthly-to-seasonal climate forecasts with a land surface model for various target basins. The portal also houses a reservoir allocation model that allows water managers to explore different release policies in meeting the system constraints and target storages conditioned on the forecasts. The talk will also demonstrate how past events (e.g., 2007-2008 drought) could be proactively monitored and managed to improve decision making in water and agricultural sectors over the Southeast US. Challenges in utilizing the portal information from institutional and operational perspectives will also be presented.

River Stream-Flow and Zayanderoud Reservoir Operation Modeling Using the Fuzzy Inference System

Directory of Open Access Journals (Sweden)

Saeed Jamali

2007-12-01

Full Text Available The Zayanderoud basin is located in the central plateau of Iran. As a result of population increase and agricultural and industrial developments, water demand on this basin has increased extensively. Given the importance of reservoir operation in water resource and management studies, the performance of fuzzy inference system (FIS for Zayanderoud reservoir operation is investigated in this paper. The model of operation consists of two parts. In the first part, the seasonal river stream-flow is forecasted using the fuzzy rule-based system. The southern oscillated index, rain, snow, and discharge are inputs of the model and the seasonal river stream-flow its output. In the second part, the operation model is constructed. The amount of releases is first optimized by a nonlinear optimization model and then the rule curves are extracted using the fuzzy inference system. This model operates on an "if-then" principle, where the "if" is a vector of fuzzy permits and "then" is the fuzzy result. The reservoir storage capacity, inflow, demand, and year condition factor are used as permits. Monthly release is taken as the consequence. The Zayanderoud basin is investigated as a case study. Different performance indices such as reliability, resiliency, and vulnerability are calculated. According to results, FIS works more effectively than the traditional reservoir operation methods such as standard operation policy (SOP or linear regression.

On the Techa’s reservoirs cascade influence on the long-term forecast of the Techa river radioactive contamination

Directory of Open Access Journals (Sweden)

S. S. Utkin

2016-01-01

Full Text Available In 1949–1956 years, the Techa river was exposed to the intense radioactive contamination, which consequences are not overcome up to now. Currently, the Techa Cascade of Water Reservoirs is the only source of contamination of this river that could be managed. In February 2016 the Chief Executive Officer of the State Corporation “ROSATOM” approved the «Strategic master-plan on the solution of the problems of the Techa Reservoir Cascade» providing a novel look at an issue of remediation of the Techa river. The aim of the article is the implementation of the modern radiation protection system to the existing or potential exposure situations of public residing near the Techa river and an analysis of possible features, events, and processes considered in the longterm forecasts performed in the field of public radiation safety. Although the current radiation state of the Techa River is relatively stable, the task of refining the traditional phenomenological retrospective analysis covering the assessment of the past and current radiation exposure and environmental impacts is considered quite relevant. The Calculation- monitoring complex “TCR-Prognoz” was developed in the framework of the “Strategic Master Plan”. This complex enables to evaluate multivariate scenario calculations resulting in long-term forecasts of radioactive contamination levels in the Techa River and its floodplain, depending on various sets of environmental conditions and anthropogenic factors. Complex radiation surveys to define the detailed character and the time frames of economic activities permitted under the existing radiation safety requirements in the floodplain of the Techa river are recommended to be started after 2020. By this time, the first steady effects associated with the “Strategic Master Plan” implementation will become evident, including those resulting from the efforts aimed at simultaneous minimization of radionuclide

Adaptive Regulation of the Northern California Reservoir System for Water, Energy, and Environmental Management

Science.gov (United States)

Georgakakos, A. P.; Kistenmacher, M.; Yao, H.; Georgakakos, K. P.

2014-12-01

The 2014 National Climate Assessment of the US Global Change Research Program emphasizes that water resources managers and planners in most US regions will have to cope with new risks, vulnerabilities, and opportunities, and recommends the development of adaptive capacity to effectively respond to the new water resources planning and management challenges. In the face of these challenges, adaptive reservoir regulation is becoming all the more ncessary. Water resources management in Northern California relies on the coordinated operation of several multi-objective reservoirs on the Trinity, Sacramento, American, Feather, and San Joaquin Rivers. To be effective, reservoir regulation must be able to (a) account for forecast uncertainty; (b) assess changing tradeoffs among water uses and regions; and (c) adjust management policies as conditions change; and (d) evaluate the socio-economic and environmental benefits and risks of forecasts and policies for each region and for the system as a whole. The Integrated Forecast and Reservoir Management (INFORM) prototype demonstration project operated in Northern California through the collaboration of several forecast and management agencies has shown that decision support systems (DSS) with these attributes add value to stakeholder decision processes compared to current, less flexible management practices. Key features of the INFORM DSS include: (a) dynamically downscaled operational forecasts and climate projections that maintain the spatio-temporal coherence of the downscaled land surface forcing fields within synoptic scales; (b) use of ensemble forecast methodologies for reservoir inflows; (c) assessment of relevant tradeoffs among water uses on regional and local scales; (d) development and evaluation of dynamic reservoir policies with explicit consideration of hydro-climatic forecast uncertainties; and (e) focus on stakeholder information needs.This article discusses the INFORM integrated design concept, underlying

Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

Science.gov (United States)

Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

2017-03-01

Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

Fluvial facies reservoir productivity prediction method based on principal component analysis and artificial neural network

Directory of Open Access Journals (Sweden)

Pengyu Gao

2016-03-01

Full Text Available It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

Advanced productivity forecast using petrophysical wireline data calibrated with MDT tests and numerical reservoir simulation

Energy Technology Data Exchange (ETDEWEB)

Andre, Carlos de [PETROBRAS, Rio de Janeiro, RJ (Brazil); Canas, Jesus A.; Low, Steven; Barreto, Wesley [Schlumberger, Houston, TX (United States)

2004-07-01

This paper describes an integrated and rigorous approach for viscous and middle oil reservoir productivity evaluation using petrophysical models calibrated with permeability derived from mini tests (Dual Packer) and Vertical Interference Tests (VIT) from open hole wire line testers (MDT SLB TM). It describes the process from Dual Packer Test and VIT pre-job design, evaluation via analytical and inverse simulation modeling, calibration and up scaling of petrophysical data into a numerical model, history matching of Dual Packer Tests and VIT with numerical simulation modeling. Finally, after developing a dynamic calibrated model, we perform productivity forecasts of different well configurations (vertical, horizontal and multilateral wells) for several deep offshore oil reservoirs in order to support well testing activities and future development strategies. The objective was to characterize formation static and dynamic properties early in the field development process to optimize well testing design, extended well test (EWT) and support the development strategies in deep offshore viscous oil reservoirs. This type of oil has limitations to flow naturally to surface and special lifting equipment is required for smooth optimum well testing/production. The integrated analysis gave a good overall picture of the formation, including permeability anisotropy and fluid dynamics. Subsequent analysis of different well configurations and lifting schemes allows maximizing formation productivity. The simulation and calibration results are compared to measured well test data. Results from this work shows that if the various petrophysical and fluid properties sources are integrated properly an accurate well productivity model can be achieved. If done early in the field development program, this time/knowledge gain could reduce the risk and maximize the development profitability of new blocks (value of the information). (author)

Real-time reservoir operation considering non-stationary inflow prediction

Science.gov (United States)

Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

2011-12-01

Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

Evaluation of Management of Water Releases for Painted Rocks Reservoir, Bitterroot River, Montana, 1983-1986, Final Report.

Energy Technology Data Exchange (ETDEWEB)

Spoon, Ronald L. (Montana Department of Fish, Wildlife and Parks, Missoula, MT)

1987-06-01

This study was initiated in July, 1983 to develop a water management plan for the release of water purchased from Painted Rocks Reservoir. Releases were designed to provide optimum benefits to the Bitterroot River fishery. Fisheries, habitat, and stream flow information was gathered to evaluate the effectiveness of these supplemental releases in improving trout populations in the Bitterroot River. The study was part of the Northwest Power Planning Council's Fish and Wildlife Program and was funded by the Bonneville Power Administration. This report presents data collected from 1983 through 1986.

Streamflow Forecasting Using Nuero-Fuzzy Inference System

Science.gov (United States)

Nanduri, U. V.; Swain, P. C.

2005-12-01

The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A

Inductive reasoning and forecasting of population dynamics of Cylindrospermopsis raciborskii in three sub-tropical reservoirs by evolutionary computation.

Science.gov (United States)

Recknagel, Friedrich; Orr, Philip T; Cao, Hongqing

2014-01-01

Seven-day-ahead forecasting models of Cylindrospermopsis raciborskii in three warm-monomictic and mesotrophic reservoirs in south-east Queensland have been developed by means of water quality data from 1999 to 2010 and the hybrid evolutionary algorithm HEA. Resulting models using all measured variables as inputs as well as models using electronically measurable variables only as inputs forecasted accurately timing of overgrowth of C. raciborskii and matched well high and low magnitudes of observed bloom events with 0.45≤r 2 >0.61 and 0.4≤r 2 >0.57, respectively. The models also revealed relationships and thresholds triggering bloom events that provide valuable information on synergism between water quality conditions and population dynamics of C. raciborskii. Best performing models based on using all measured variables as inputs indicated electrical conductivity (EC) within the range of 206-280mSm -1 as threshold above which fast growth and high abundances of C. raciborskii have been observed for the three lakes. Best models based on electronically measurable variables for the Lakes Wivenhoe and Somerset indicated a water temperature (WT) range of 25.5-32.7°C within which fast growth and high abundances of C. raciborskii can be expected. By contrast the model for Lake Samsonvale highlighted a turbidity (TURB) level of 4.8 NTU as indicator for mass developments of C. raciborskii. Experiments with online measured water quality data of the Lake Wivenhoe from 2007 to 2010 resulted in predictive models with 0.61≤r 2 >0.65 whereby again similar levels of EC and WT have been discovered as thresholds for outgrowth of C. raciborskii. The highest validity of r 2 =0.75 for an in situ data-based model has been achieved after considering time lags for EC by 7 days and dissolved oxygen by 1 day. These time lags have been discovered by a systematic screening of all possible combinations of time lags between 0 and 10 days for all electronically measurable variables. The so

Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain)

Energy Technology Data Exchange (ETDEWEB)

Canovas, Carlos Ruiz, E-mail: carlos.ruiz@dgeo.uhu.es [Institute of Environmental Assessment and Water Research (IDAeA-CSIC). c/Jordi Girona 18-26, 08034 Barcelona (Spain); Department of Geodynamics and Paleontology, University of Huelva, Facultad de Ciencias Experimentales, Avenida 3 de Marzo s/n, 21071 Huelva (Spain); Olias, Manuel [Department of Physical, Chemical and Natural Systems, University Pablo de Olavide. Ctra.de Utrera km 1, 41013, Sevilla (Spain); Vazquez-Sune, Enric; Ayora, Carlos [Institute of Environmental Assessment and Water Research (IDAeA-CSIC). c/Jordi Girona 18-26, 08034 Barcelona (Spain); Nieto, Jose Miguel [Department of Geology, University of Huelva, Facultad de Ciencias Experimentales, Avenida 3 de Marzo s/n, 21071 Huelva (Spain)

2012-02-01

The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12-16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2-4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. - Highlights: Black-Right-Pointing-Pointer We study the influence of freshwater releases on the

Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain)

International Nuclear Information System (INIS)

Cánovas, Carlos Ruiz; Olias, Manuel; Vazquez-Suñé, Enric; Ayora, Carlos; Nieto, Jose Miguel

2012-01-01

The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12–16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2–4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. - Highlights: ► We study the influence of freshwater releases on the acidic Tinto river

Uncertainty analysis of hydro-meteorological forecasts

OpenAIRE

Grythe, Karl Kristian; Gao, Yukun

2010-01-01

Masteroppgave i informasjons- og kommunikasjonsteknologi 2010 – Universitetet i Agder, Grimstad Meteorological and hydrological forecasts are very important to human’s life which concerns agriculture, industry, transport, etc. The Nordic hydropower industry use and develop hydrological forecasting models to make predictions of rivers steam flow. The quantity of incoming stream flow is important to the electricity production because excessive water in reservoir will cause flood ...

Forecasting analysis of runoff for reservoir regulation of dams and weirs in terms of hydro power plant operation

International Nuclear Information System (INIS)

Maradjieva, Mariana; Nikolov, Nikola

2008-01-01

In order to meet the needs of Hydropower Plant (HPP) production new algorithms and software were developed for daily, seasonal, annual and long-term control of the runoff for the design of dam and weirs. This control is carried out for monitored periods from 20 to 50 years. The control depends on economic considerations, namely that the accepted probability of required water power is 90%, i.e. concerning the runoff and in this way for the useful volume of water dams. The research is accomplished by a design with the observations. First the hydrometric stations are selected at the available analogy with the building project and then the correlative connection is found assessed by general and true correlative coefficients. The transferring to the project of the observations for the average annual and average monthly water discharges is made with the coefficient of the analogy. The theoretical probability curves are chosen with a minimum dispersion. By the last curves the average monthly distributions are settled with probability from 2% to 90% by statistical method. During the investigated period of the regulation the volumes of discharge, overflow and shortage are calculated as and the determination for the accepted volume of the reservoir if the normative probability of the need is executed. As well the power output of the HPP and its participation in the coverage of the charge diagram on the peak load, under peak load, daily and nightly part are determined in separate observed or forecasting periods. The upper problems about the design and the operation of HPP, water output, reservoir volume and coverage of the charge diagram are solved by iterations. Practical examples are given for the runoff and for the time forecasting system.

Operational Hydrologic Forecasts in the Columbia River Basin

Science.gov (United States)

Shrestha, K. Y.; Curry, J. A.; Webster, P. J.; Toma, V. E.; Jelinek, M.

2013-12-01

The Columbia River Basin (CRB) covers an area of ~670,000 km2 and stretches across parts of seven U.S. states and one Canadian province. The basin is subject to a variable climate, and moisture stored in snowpack during the winter is typically released in spring and early summer. These releases contribute to rapid increases in flow. A number of impoundments have been constructed on the Columbia River main stem and its tributaries for the purposes of flood control, navigation, irrigation, recreation, and hydropower. Storage reservoirs allow water managers to adjust natural flow patterns to benefit water and energy demands. In the past decade, the complexity of water resource management issues in the basin has amplified the importance of streamflow forecasting. Medium-range (1-10 day) numerical weather forecasts of precipitation and temperature can be used to drive hydrological models. In this work, probabilistic meteorological variables from the European Center for Medium Range Weather Forecasting (ECMWF) are used to force the Variable Infiltration Capacity (VIC) model. Soil textures were obtained from FAO data; vegetation types / land cover information from UMD land cover data; stream networks from USGS HYDRO1k; and elevations from CGIAR version 4 SRTM data. The surface energy balance in 0.25° (~25 km) cells is closed through an iterative process operating at a 6 hour timestep. Output fluxes from a number of cells in the basin are combined through one-dimensional flow routing predicated on assumptions of linearity and time invariance. These combinations lead to daily mean streamflow estimates at key locations throughout the basin. This framework is suitable for ingesting daily numerical weather prediction data, and was calibrated using USGS mean daily streamflow data at the Dalles Dam (TDA). Operational streamflow forecasts in the CRB have been active since October 2012. These are 'naturalized' or unregulated forecasts. In 2013, increases of ~2600 m3/s (~48% of

Development of gas and gas condensate reservoirs

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-12-01

In the study of gas reservoir development, the first year topics are restricted on reservoir characterization. There are two types of reservoir characterization. One is the reservoir formation characterization and the other is the reservoir fluid characterization. For the reservoir formation characterization, calculation of conditional simulation was compared with that of unconditional simulation. The results of conditional simulation has higher confidence level than the unconditional simulation because conditional simulation considers the sample location as well as distance correlation. In the reservoir fluid characterization, phase behavior calculations revealed that the component grouping is more important than the increase of number of components. From the liquid volume fraction with pressure drop, the phase behavior of reservoir fluid can be estimated. The calculation results of fluid recombination, constant composition expansion, and constant volume depletion are matched very well with the experimental data. In swelling test of the reservoir fluid with lean gas, the accuracy of dew point pressure forecast depends on the component characterization. (author). 28 figs., 10 tabs.

Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain).

Science.gov (United States)

Cánovas, Carlos Ruiz; Olias, Manuel; Vazquez-Suñé, Enric; Ayora, Carlos; Miguel Nieto, Jose

2012-02-01

The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12-16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2-4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. Copyright © 2011 Elsevier B.V. All rights reserved.

Fundamental Study of Disposition and Release of Methane in a Shale Gas Reservoir

Energy Technology Data Exchange (ETDEWEB)

Wang, Yifeng [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Xiong, Yongliang [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Repository Performance; Criscenti, Louise J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Ho, Tuan Ahn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Weck, Philippe F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Storage and Transportation Technology; Ilgen, Anastasia G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Matteo, Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Kruichak, Jessica N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Mills, Melissa M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Dewers, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geomechanics; Gordon, Margaret E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Materials, Devices and Energy Technologies; Akkutlu, Yucel [Texas A & M Univ., College Station, TX (United States). Dept. of Petroleum Engineering

2016-09-01

simulations also indicate that a significant fraction (3 - 35%) of methane deposited in kerogen can potentially become trapped in isolated nanopores and thus not recoverable. We have successfully established experimental capabilities for measuring gas sorption and desorption on shale and model materials under a wide range of physical and chemical conditions. Both low and high pressure measurements show significant sorption of CH₄ and CO₂ onto clays, implying that methane adsorbed on clay minerals could contribute a significant portion of gas-in-place in an unconventional reservoir. We have also studied the potential impact of the interaction of shale with hydrofracking fluid on gas sorption. We have found that the CH₄-CO₂ sorption capacity for the reacted sample is systematically lower (by a factor of ~2) than that for the unreacted (raw) sample. This difference in sorption capacity may result from a mineralogical or surface chemistry change of the shale sample induced by fluid-rock interaction. Our results shed a new light on mechanistic understanding gas release and production decline in unconventional reservoirs.

Restoring Natural Streamflow Variability by Modifying Multi-purpose Reservoir Operation

Science.gov (United States)

Shiau, J.

2010-12-01

Multi-purpose reservoirs typically provide benefits of water supply, hydroelectric power, and flood mitigation. Hydroelectric power generations generally do not consume water. However, temporal distribution of downstream flows is highly changed due to hydro-peaking effects. Associated with offstream diversion of water supplies for municipal, industrial, and agricultural requirements, natural streamflow characteristics of magnitude, duration, frequency, timing, and rate of change is significantly altered by multi-purpose reservoir operation. Natural flow regime has long been recognized a master factor for ecosystem health and biodiversity. Restoration of altered flow regime caused by multi-purpose reservoir operation is the main objective of this study. This study presents an optimization framework that modifying reservoir operation to seeking balance between human and environmental needs. The methodology presented in this study is applied to the Feitsui Reservoir, located in northern Taiwan, with main purpose of providing stable water-supply and auxiliary purpose of electricity generation and flood-peak attenuation. Reservoir releases are dominated by two decision variables, i.e., duration of water releases for each day and percentage of daily required releases within the duration. The current releasing policy of the Feitsui Reservoir releases water for water-supply and hydropower purposes during 8:00 am to 16:00 pm each day and no environmental flows releases. Although greater power generation is obtained by 100% releases distributed within 8-hour period, severe temporal alteration of streamflow is observed downstream of the reservoir. Modifying reservoir operation by relaxing these two variables and reserve certain ratio of streamflow as environmental flow to maintain downstream natural variability. The optimal reservoir releasing policy is searched by the multi-criterion decision making technique for considering reservoir performance in terms of shortage ratio

Requirements and benefits of flow forecasting for improving hydropower generation

NARCIS (Netherlands)

Dong, Xiaohua; Vrijling, J.K.; Dohmen-Janssen, Catarine M.; Ruigh, E.; Booij, Martijn J.; Stalenberg, B.; Hulscher, Suzanne J.M.H.; van Gelder, P.H.A.J.M.; Verlaan, M.; Zijderveld, A.; Waarts, P.

2005-01-01

This paper presents a methodology to identify the required lead time and accuracy of flow forecasting for improving hydropower generation of a reservoir, by simulating the benefits (in terms of electricity generated) obtained from the forecasting with varying lead times and accuracies. The

Verification of Ensemble Forecasts for the New York City Operations Support Tool

Science.gov (United States)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble

Formation and forecast of the daily price of the electric power in the chain Nare-Guatape-San Carlos

International Nuclear Information System (INIS)

Romero, Alejandro; Carvajal, Luis

2003-01-01

This work shows three different methodologies for the understanding and forecast of the electric energy prices in the chain Nare - Guatape - San Carlos: lineal multivariate model, autoregressive deterministic model and Fourier series decomposition. The electric energy price depends basically of the reservoir level and river flow, not only its own but the reservoir down and up, waters. About prices forecast, they can be modeled with an autoregressive process. Prices forecast follows the tendency and captures with acceptable precision the maximum prices due especially to the low hydrology and price variability for daily and weekly regulation reservoirs

Great landslide events in Italian artificial reservoirs

Directory of Open Access Journals (Sweden)

A. Panizzo

2005-01-01

Full Text Available The empirical formulations to forecast landslide generated water waves, recently defined in the framework of a research program funded by the Italian National Dam Office RID (Registro Italiano Dighe, are here used to study three real cases of subaerial landslides which fell down italian artificial reservoirs. It is well known that impulse water waves generated by landslides constitute a very dangerous menace for human communities living in the shoreline of the artificial basin or downstream the dam. In 1963, the menace became tragedy, when a 270 millions m3 landslide fell down the Vajont reservoir (Italy, generated an impulse wave which destroyed the city of Longarone, and killed 2000 people. The paper is aimed at presenting the very satisfactorily reproduction of the events at hand by using forecasting formulations.  

Great landslide events in Italian artificial reservoirs

Science.gov (United States)

Panizzo, A.; de Girolamo, P.; di Risio, M.; Maistri, A.; Petaccia, A.

2005-09-01

The empirical formulations to forecast landslide generated water waves, recently defined in the framework of a research program funded by the Italian National Dam Office RID (Registro Italiano Dighe), are here used to study three real cases of subaerial landslides which fell down italian artificial reservoirs. It is well known that impulse water waves generated by landslides constitute a very dangerous menace for human communities living in the shoreline of the artificial basin or downstream the dam. In 1963, the menace became tragedy, when a 270 millions m3 landslide fell down the Vajont reservoir (Italy), generated an impulse wave which destroyed the city of Longarone, and killed 2000 people. The paper is aimed at presenting the very satisfactorily reproduction of the events at hand by using forecasting formulations.

Microchips and controlled-release drug reservoirs.

Science.gov (United States)

Staples, Mark

2010-01-01

This review summarizes and updates the development of implantable microchip-containing devices that control dosing from drug reservoirs integrated with the devices. As the expense and risk of new drug development continues to increase, technologies that make the best use of existing therapeutics may add significant value. Trends of future medical care that may require advanced drug delivery systems include individualized therapy and the capability to automate drug delivery. Implantable drug delivery devices that promise to address these anticipated needs have been constructed in a variety of ways using micro- and nanoelectromechanical systems (MEMS or NEMS)-based technology. These devices expand treatment options for addressing unmet medical needs related to dosing. Within the last few years, advances in several technologies (MEMS or NEMS fabrication, materials science, polymer chemistry, and data management) have converged to enable the construction of miniaturized implantable devices for controlled delivery of therapeutic agents from one or more reservoirs. Suboptimal performance of conventional dosing methods in terms of safety, efficacy, pain, or convenience can be improved with advanced delivery devices. Microchip-based implantable drug delivery devices allow localized delivery by direct placement of the device at the treatment site, delivery on demand (emergency administration, pulsatile, or adjustable continuous dosing), programmable dosing cycles, automated delivery of multiple drugs, and dosing in response to physiological and diagnostic feedback. In addition, innovative drug-medical device combinations may protect labile active ingredients within hermetically sealed reservoirs. Copyright (c) 2010 John Wiley & Sons, Inc.

Design and development of bio-inspired framework for reservoir operation optimization

Science.gov (United States)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

Forecasting production in Liquid Rich Shale plays

Science.gov (United States)

Nikfarman, Hanieh

Production from Liquid Rich Shale (LRS) reservoirs is taking center stage in the exploration and production of unconventional reservoirs. Production from the low and ultra-low permeability LRS plays is possible only through multi-fractured horizontal wells (MFHW's). There is no existing workflow that is applicable to forecasting multi-phase production from MFHW's in LRS plays. This project presents a practical and rigorous workflow for forecasting multiphase production from MFHW's in LRS reservoirs. There has been much effort in developing workflows and methodology for forecasting in tight/shale plays in recent years. The existing workflows, however, are applicable only to single phase flow, and are primarily used in shale gas plays. These methodologies do not apply to the multi-phase flow that is inevitable in LRS plays. To account for complexities of multiphase flow in MFHW's the only available technique is dynamic modeling in compositional numerical simulators. These are time consuming and not practical when it comes to forecasting production and estimating reserves for a large number of producers. A workflow was developed, and validated by compositional numerical simulation. The workflow honors physics of flow, and is sufficiently accurate while practical so that an analyst can readily apply it to forecast production and estimate reserves in a large number of producers in a short period of time. To simplify the complex multiphase flow in MFHW, the workflow divides production periods into an initial period where large production and pressure declines are expected, and the subsequent period where production decline may converge into a common trend for a number of producers across an area of interest in the field. Initial period assumes the production is dominated by single-phase flow of oil and uses the tri-linear flow model of Erdal Ozkan to estimate the production history. Commercial software readily available can simulate flow and forecast production in this

Comparison of Strategies for Climate Change Adaptation of Water Supply and Flood Control Reservoirs

Science.gov (United States)

Ng, T. L.; Yang, P.; Bhushan, R.

2016-12-01

With climate change, streamflows are expected to become more fluctuating, with more frequent and intense floods and droughts. This complicates reservoir operation, which is highly sensitive to inflow variability. We make a comparative evaluation of three strategies for adapting reservoirs to climate-induced shifts in streamflow patterns. Specifically, we examine the effectiveness of (i) expanding the capacities of reservoirs by way of new off-stream reservoirs, (ii) introducing wastewater reclamation to augment supplies, and (iii) improving real-time streamflow forecasts for more optimal decision-making. The first two are hard strategies involving major infrastructure modifications, while the third a soft strategy entailing adjusting the system operation. A comprehensive side-by-side comparison of the three strategies is as yet lacking in the literature despite the many past studies investigating the strategies individually. To this end, we developed an adaptive forward-looking linear program that solves to yield the optimal decisions for the current time as a function of an ensemble forecast of future streamflows. Solving the model repeatedly on a rolling basis with regular updating of the streamflow forecast simulates the system behavior over the entire operating horizon. Results are generated for two hypothetical water supply and flood control reservoirs of differing inflows and demands. Preliminary findings suggest that of the three strategies, improving streamflow forecasts to be most effective in mitigating the effects of climate change. We also found that, in average terms, both additional reservoir capacity and wastewater reclamation have potential to reduce water shortage and downstream flooding. However, in the worst case, the potential of the former to reduce water shortage is limited, and similarly so the potential of the latter to reduce downstream flooding.

Tailored ramp-loading via shock release of stepped-density reservoirs

International Nuclear Information System (INIS)

Prisbrey, Shon T.; Park, Hye-Sook; Remington, Bruce A.; Cavallo, Robert; May, Mark; Pollaine, Stephen M.; Rudd, Robert; Maddox, Brian; Comley, Andrew; Fried, Larry; Blobaum, Kerri; Wallace, Russ; Wilson, Mike; Swift, David; Satcher, Joe; Kalantar, Dan; Perry, Ted; Giraldez, Emilio; Farrell, Michael; Nikroo, Abbas

2012-01-01

The concept of a gradient piston drive has been extended from that of a single component reservoir, such as a high explosive, to that of a multi-component reservoir that utilizes low density foams and large shocks to achieve high pressures (∼3.5 mbar) and controlled pressure vs. time profiles on a driven sample. Simulated and experimental drives shaped through the use of multiple component (including carbonized resorcinol formaldehyde and SiO 2 foam) reservoirs are compared. Individual density layers in a multiple component reservoir are shown to correlate with velocity features in the measured drive which enables the ability to tune a pressure drive by adjusting the components of the reservoir. Pre-shot simulations are shown to be in rough agreement with the data, but post-shot simulations involving the use of simulated plasma drives were needed to achieve an exact match. Results from a multiple component reservoir shot (∼3.5 mbar) at the National Ignition Facility are shown.

In the Way of Peacemaker Guide Curve between Water Supply and Flood Control for Short Term Reservoir Operation

Science.gov (United States)

Uysal, G.; Sensoy, A.; Yavuz, O.; Sorman, A. A.; Gezgin, T.

2012-04-01

taking inflow, elevation, precipitation and snow water equivalent into consideration to propose alternative simulations as a decision support system. After that, the releases are subjected to user-defined rules. Thus, previous year reservoir simulations are compared with observed reservoir levels and releases. Hypothetical flood scenarios are tested in case of different storm event timing and sizing. Numerical weather prediction data of Mesoscale Model 5 (MM5) can be used for temperature and precipitation forecasts that will form the inputs for a hydrological model. The estimated flows can be used for real time short term decisions for reservoir simulation based on variable guide curve and user defined rules.

Reservoir Operating Rule Optimization for California's Sacramento Valley

Directory of Open Access Journals (Sweden)

Timothy Nelson

2016-03-01

Full Text Available doi: http://dx.doi.org/10.15447/sfews.2016v14iss1art6Reservoir operating rules for water resource systems are typically developed by combining intuition, professional discussion, and simulation modeling. This paper describes a joint optimization–simulation approach to develop preliminary economically-based operating rules for major reservoirs in California’s Sacramento Valley, based on optimized results from CALVIN, a hydro-economic optimization model. We infer strategic operating rules from the optimization model results, including storage allocation rules to balance storage among multiple reservoirs, and reservoir release rules to determine monthly release for individual reservoirs. Results show the potential utility of considering previous year type on water availability and various system and sub-system storage conditions, in addition to normal consideration of local reservoir storage, season, and current inflows. We create a simple simulation to further refine and test the derived operating rules. Optimization model results show particular insights for balancing the allocation of water storage among Shasta, Trinity, and Oroville reservoirs over drawdown and refill seasons, as well as some insights for release rules at major reservoirs in the Sacramento Valley. We also discuss the applicability and limitations of developing reservoir operation rules from optimization model results.

Trade-off analysis of discharge-desiltation-turbidity and ANN analysis on sedimentation of a combined reservoir-reach system under multi-phase and multi-layer conjunctive releasing operation

Science.gov (United States)

Huang, Chien-Lin; Hsu, Nien-Sheng; Wei, Chih-Chiang; Yao, Chun-Hao

2017-10-01

Multi-objective reservoir operation considering the trade-off of discharge-desiltation-turbidity during typhoons and sediment concentration (SC) simulation modeling are the vital components for sustainable reservoir management. The purposes of this study were (1) to analyze the multi-layer release trade-offs between reservoir desiltation and intake turbidity of downstream purification plants and thus propose a superior conjunctive operation strategy and (2) to develop ANFIS-based (adaptive network-based fuzzy inference system) and RTRLNN-based (real-time recurrent learning neural networks) substitute SC simulation models. To this end, this study proposed a methodology to develop (1) a series of multi-phase and multi-layer sediment-flood conjunctive release modes and (2) a specialized SC numerical model for a combined reservoir-reach system. The conjunctive release modes involve (1) an optimization model where the decision variables are multi-phase reduction/scaling ratios and the timings to generate a superior total release hydrograph for flood control (Phase I: phase prior to flood arrival, Phase II/III: phase prior to/subsequent to peak flow) and (2) a combination method with physical limitations regarding separation of the singular hydrograph into multi-layer release hydrographs for sediment control. This study employed the featured signals obtained from statistical quartiles/sediment duration curve in mesh segmentation, and an iterative optimization model with a sediment unit response matrix and corresponding geophysical-based acceleration factors, for efficient parameter calibration. This research applied the developed methodology to the Shihmen Reservoir basin in Taiwan. The trade-off analytical results using Typhoons Sinlaku and Jangmi as case examples revealed that owing to gravity current and re-suspension effects, Phase I + II can de-silt safely without violating the intake's turbidity limitation before reservoir discharge reaches 2238 m3/s; however

Application of seasonal forecasting for the drought forecasting in Catalonia (Spain)

Science.gov (United States)

Llasat, Maria-Carmen; Zaragoza, Albert; Aznar, Blanca; Cabot, Jordi

2010-05-01

Low flows and droughts are a hydro-climatic feature in Spain (Alvarez et al, 2008). The construction of dams as water reservoirs has been a usual tool to manage the water resources for agriculture and livestock, industries and human needs (MIMAM, 2000, 2007). The last drought that has affected Spain has last four years in Catalonia, from 2004 to the spring of 2008, and it has been particularly hard as a consequence of the precipitation deficit in the upper part of the rivers that nourish the main dams. This problem increases when the water scarcity affects very populated areas, like big cities. The Barcelona city, with more than 3.000.000 people concentrated in the downtown and surrounding areas is a clear example. One of the objectives of the SOSTAQUA project is to improve the water resources management in real time, in order to improve the water supply in the cities in the framework of sustainable development. The work presented here deals with the application of seasonal forecasting to improve the water management in Catalonia, particularly in drought conditions. A seasonal prediction index has been created as a linear combination of climatic data and the ECM4 prediction that has been validated too. This information has implemented into a hydrological model and it has been applied to the last drought considering the real water demands of population, as well as to the water storage evolution in the last months. It has been found a considerable advance in the forecasting of water volume into reservoirs. The advantage of this methodology is that it only requires seasonal forecasting free through internet. Due to the fact that the principal rivers that supply water to Barcelona, birth on the Pyrenees and Pre-Pyrenees region, the analysis and precipitation forecasting is focused on this region (Zaragoza, 2008).

The management of subsurface uncertainty using probabilistic modeling of life cycle production forecasts and cash flows

International Nuclear Information System (INIS)

Olatunbosun, O. O.

1998-01-01

The subject pertains to the implementation of the full range of subsurface uncertainties in life cycle probabilistic forecasting and its extension to project cash flows using the methodology of probabilities. A new tool has been developed in the probabilistic application of Crystal-Ball which can model reservoir volumetrics, life cycle production forecasts and project cash flows in a single environment. The tool is modular such that the volumetrics and cash flow modules are optional. Production forecasts are often generated by applying a decline equation to single best estimate values of input parameters such as initial potential, decline rate, abandonment rate etc -or sometimes by results of reservoir simulation. This new tool provides a means of implementing the full range of uncertainties and interdependencies of the input parameters into the production forecasts by defining the input parameters as probability density functions, PDFs and performing several iterations to generate an expectation curve forecast. Abandonment rate is implemented in each iteration via a link to an OPEX model. The expectation curve forecast is input into a cash flow model to generate a probabilistic NPV. Base case and sensitivity runs from reservoir simulation can likewise form the basis for a probabilistic production forecast from which a probabilistic cash flow can be generated. A good illustration of the application of this tool is in the modelling of the production forecast for a well that encounters its target reservoirs in OUT/ODT situation and thus has significant uncertainties. The uncertainty in presence and size (if present) of gas cap and dependency between ultimate recovery and initial potential amongst other uncertainties can be easily implemented in the production forecast with this tool. From the expectation curve forecast, a probabilistic NPV can be easily generated. Possible applications of this tool include: i. estimation of range of actual recoverable volumes based

Study of the impact of the uncertainties in petroleum reservoir behavior; Estudo do impacto de incertezas no desempenho de reservatorios de petroleo

Energy Technology Data Exchange (ETDEWEB)

Loschiavo, Roberto [PETROBRAS S.A., SE/AL (Brazil). Exploracao e Producao]. E-mail: rloschiavo@ep-seal.petrobras.com.br; Schiozer, Denis J. [Universidade Estadual de Campinas, SP (Brazil). Centro de Estudo do Petroleo (CEPETRO)]. E-mail: denis@cepetro.unicamp.br; Steagall, Daniel Escobar [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica]. E-mail: steagall@dep.fem.unicamp.br

2000-07-01

Economic evaluation of a project as well as facilities design for oil exploitation is, in general, based on production forecasts. Since production forecast depends on several parameters that are not completely known, one should take a probabilistic approach for reservoir modeling and numerical flow simulation. With this research we propose a procedure to estimate probabilistic production forecasts profiles based on the decision tree technique. The most influencing parameters of a reservoir model are identified and combined to generate a number of realizations of the reservoirs. The combination of each branch of the decision tree defines the probability associated to each reservoir model. A computer program was developed to automatically generate the reservoir models, submit them to the numerical simulator, and process the results. Parallel computing was used to improve the performance of the procedure. (author)

Matrix and reservoir-type multipurpose vaginal rings for controlled release of dapivirine and levonorgestrel.

Science.gov (United States)

Boyd, Peter; Fetherston, Susan M; McCoy, Clare F; Major, Ian; Murphy, Diarmaid J; Kumar, Sandeep; Holt, Jonathon; Brimer, Andrew; Blanda, Wendy; Devlin, Brid; Malcolm, R Karl

2016-09-10

A matrix-type silicone elastomer vaginal ring providing 28-day continuous release of dapivirine (DPV) - a lead candidate human immunodeficiency virus type 1 (HIV-1) microbicide compound - has recently demonstrated moderate levels of protection in two Phase III clinical studies. Here, next-generation matrix and reservoir-type silicone elastomer vaginal rings are reported for the first time offering simultaneous and continuous in vitro release of DPV and the contraceptive progestin levonorgestrel (LNG) over a period of between 60 and 180days. For matrix-type vaginal rings comprising initial drug loadings of 100, 150 or 200mg DPV and 0, 16 or 32mg LNG, Day 1 daily DPV release values were between 4132 and 6113μg while Day 60 values ranged from 284 to 454μg. Daily LNG release ranged from 129 to 684μg on Day 1 and 2-91μg on Day 60. Core-type rings comprising one or two drug-loaded cores provided extended duration of in vitro release out to 180days, and maintained daily drug release rates within much narrower windows (either 75-131μg/day or 37-66μg/day for DPV, and either 96-150μg/day or 37-57μg/day for LNG, depending on core ring configuration and ignoring initial lag release effect for LNG) compared with matrix-type rings. The data support the continued development of these devices as multi-purpose prevention technologies (MPTs) for HIV prevention and long-acting contraception. Copyright © 2016 Elsevier B.V. All rights reserved.

Reservoirs on the mountain rivers and their safety

Directory of Open Access Journals (Sweden)

Ts.Z. Basilashvili

2016-06-01

Full Text Available Water resource issues and problems in the world's developing countries, present special challenges, as development of these countries significantly depends on the utilization of water resources. Georgia nestled between the Black Sea, Russia, and Turkey, and surrounded by the Caucasus Mountains, occupies a unique geographic space, which gives it strategic importance far beyond its size. Though blessed by its rich hydro resources, Georgia due to its uneven distribution, experiences some problems as the demand on water frequently doesn't coincide with water provision. As a result it causes acute deficit situation. Due to the global warming of the climate, it is expected that the fresh water amount will decrease in Georgia. This is why it is necessary to approach the use of water resources in a complex way by means of water reservoirs, which will enable attaining of a large economic effect. In the mountainous conditions filling of reservoirs take place in spring time, when snow and glaciers melt. In Georgia as in mountainous country, abundant rains take place, thus causing catastrophic flooding on rivers. In summer and winter water amount decreases 10 times and irrigation, water provision and energy production is impeded. Thus, the lack of water just like the excess amount of water causes damage. This is why it is needed to forecast water amount in water reservoirs for different periods of the year. But in a complex, mountainous terrain operative data of hydrometeorology is not sufficient for application of modern mathematical methods. We have elaborated multiple-factor statistical model for a forecast, which by means of different mathematical criteria and methods can simultaneously research the increase of the timeliness of forecasts and the level of their precision. We have obtained methodologies for short and long term forecasts of inflowing water properties in Georgia's main water reservoirs to further plan optimally and regulate water resources

Deterministic Echo State Networks Based Stock Price Forecasting

Directory of Open Access Journals (Sweden)

Jingpei Dan

2014-01-01

Full Text Available Echo state networks (ESNs, as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock price prediction applications. The experiment results on two benchmark datasets (Shanghai Composite Index and S&P500 demonstrate that deterministic ESNs outperform standard ESN in both accuracy and efficiency, which indicate the prospect of deterministic ESNs for financial prediction.

Uncertainties in Forecasting Streamflow using Entropy Theory

Science.gov (United States)

Cui, H.; Singh, V. P.

2017-12-01

Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

Forecasting Hoabinh Reservoir’s Incoming Flow: An Application of Neural Networks with the Cuckoo Search Algorithm

Directory of Open Access Journals (Sweden)

Jeng-Fung Chen

2014-11-01

Full Text Available The accuracy of reservoir flow forecasting has the most significant influence on the assurance of stability and annual operations of hydro-constructions. For instance, accurate forecasting on the ebb and flow of Vietnam’s Hoabinh Reservoir can aid in the preparation and prevention of lowland flooding and drought, as well as regulating electric energy. This raises the need to propose a model that accurately forecasts the incoming flow of the Hoabinh Reservoir. In this study, a solution to this problem based on neural network with the Cuckoo Search (CS algorithm is presented. In particular, we used hydrographic data and predicted total incoming flows of the Hoabinh Reservoir over a period of 10 days. The Cuckoo Search algorithm was utilized to train the feedforward neural network (FNN for prediction. The algorithm optimized the weights between layers and biases of the neuron network. Different forecasting models for the three scenarios were developed. The constructed models have shown high forecasting performance based on the performance indices calculated. These results were also compared with those obtained from the neural networks trained by the particle swarm optimization (PSO and back-propagation (BP, indicating that the proposed approach performed more effectively. Based on the experimental results, the scenario using the rainfall and the flow as input yielded the highest forecasting accuracy when compared with other scenarios. The performance criteria RMSE, MAPE, and R obtained by the CS-FNN in this scenario were calculated as 48.7161, 0.067268 and 0.8965, respectively. These results were highly correlated to actual values. It is expected that this work may be useful for hydrographic forecasting.

Evaluation of Management of Water Release for Painted Rocks Reservoir, Bitterroot River, Montana, 1984 Annual Report.

Energy Technology Data Exchange (ETDEWEB)

Lere, Mark E. (Montana Department of Fish, Wildlife and Parks, Missoula, MT)

1984-11-01

Baseline fisheries and habitat data were gathered during 1983 and 1984 to evaluate the effectiveness of supplemental water releases from Painted Rocks Reservoir in improving the fisheries resource in the Bitterroot River. Discharge relationships among main stem gaging stations varied annually and seasonally. Flow relationships in the river were dependent upon rainfall events and the timing and duration of the irrigation season. Daily discharge monitored during the summers of 1983 and 1984 was greater than median values derived at the U.S.G.S. station near Darby. Supplemental water released from Painted Rocks Reservoir totaled 14,476 acre feet in 1983 and 13,958 acre feet in 1984. Approximately 63% of a 5.66 m{sup 3}/sec test release of supplemental water conducted during April, 1984 was lost to irrigation withdrawals and natural phenomena before passing Bell Crossing. A similar loss occurred during a 5.66 m{sup 3}/sec test release conducted in August, 1984. Daily maximum temperature monitored during 1984 in the Bitterroot River averaged 11.0, 12.5, 13.9 and 13.6 C at the Darby, Hamilton, Bell and McClay stations, respectively. Chemical parameters measured in the Bitterroot River were favorable to aquatic life. Population estimates conducted in the Fall, 1983 indicated densities of I+ and older rainbow trout (Salmo gairdneri) were significantly greater in a control section than in a dewatered section (p < 0.20). Numbers of I+ and older brown trout (Salmo trutta) were not significantly different between the control and dewatered sections (p > 0.20). Population and biomass estimates for trout in the control section were 631/km and 154.4 kg/km. In the dewatered section, population and biomass estimates for trout were 253/km and 122.8 kg/km. The growth increments of back-calculated length for rainbow trout averaged 75.6 mm in the control section and 66.9mm in the dewatered section. The growth increments of back-calculated length for brown trout averaged 79.5 mm in the

Evaluating the Implications of Climate Phenomenon Indices in Supporting Reservoir Operation Using the Artificial Neural Network and Decision-Tree Methods: A Case Study on Trinity Lake in Northern California

Science.gov (United States)

Yang, T.; Akbari Asanjan, A.; Gao, X.; Sorooshian, S.

2016-12-01

Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for all kinds of purposes, including residential and industrial water supply, flood control, hydropower, and irrigation, etc. Efficient reservoir operation requires that policy makers and operators understand how reservoir inflows, available storage, and discharges are changing under different climatic conditions. Over the last decade, the uses of Artificial Intelligence and Data Mining (AI & DM) techniques in assisting reservoir management and seasonal forecasts have been increasing. Therefore, in this study, two distinct AI & DM methods, Artificial Neural Network (ANN) and Random Forest (RF), are employed and compared with respect to their capabilities of predicting monthly reservoir inflow, managing storage, and scheduling reservoir releases. A case study on Trinity Lake in northern California is conducted using long-term (over 50 years) reservoir operation records and 17 known climate phenomenon indices, i.e. PDO and ENSO, etc., as predictors. Results show that (1) both ANN and RF are capable of providing reasonable monthly reservoir storage, inflow, and outflow prediction with satisfactory statistics, and (2) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow and outflow. It is also found that reservoir storage has a consistent high autocorrelation effect, while inflow and outflow are more likely to be influenced by climate conditions. Using a Gini diversity index, RF method identifies that the reservoir discharges are associated with Southern Oscillation Index (SOI) and reservoir inflows are influenced by multiple climate phenomenon indices during different seasons. Furthermore, results also show that, during the winter season, reservoir discharges are controlled by the storage level for flood-control purposes, while, during the summer season, the flood-control operation is not as

Fuzzy rule-based model for hydropower reservoirs operation

Energy Technology Data Exchange (ETDEWEB)

Moeini, R.; Afshar, A.; Afshar, M.H. [School of Civil Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

2011-02-15

Real-time hydropower reservoir operation is a continuous decision-making process of determining the water level of a reservoir or the volume of water released from it. The hydropower operation is usually based on operating policies and rules defined and decided upon in strategic planning. This paper presents a fuzzy rule-based model for the operation of hydropower reservoirs. The proposed fuzzy rule-based model presents a set of suitable operating rules for release from the reservoir based on ideal or target storage levels. The model operates on an 'if-then' principle, in which the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. In this paper, reservoir storage, inflow, and period are used as premises and the release as the consequence. The steps involved in the development of the model include, construction of membership functions for the inflow, storage and the release, formulation of fuzzy rules, implication, aggregation and defuzzification. The required knowledge bases for the formulation of the fuzzy rules is obtained form a stochastic dynamic programming (SDP) model with a steady state policy. The proposed model is applied to the hydropower operation of ''Dez'' reservoir in Iran and the results are presented and compared with those of the SDP model. The results indicate the ability of the method to solve hydropower reservoir operation problems. (author)

Real-time data processing and inflow forecasting

International Nuclear Information System (INIS)

Olason, T.; Lafreniere, M.

1998-01-01

One of the key inputs into the short-term scheduling of hydroelectric generation is inflow forecasting which is needed for natural or unregulated inflows into various lakes, reservoirs and river sections. The forecast time step and time horizon are determined by the time step and the scheduling horizon. Acres International Ltd. has developed the Vista Decision Support System (DSS) in which the time step is one hour and the scheduling can be done up to two weeks into the future. This paper presents the basis of the operational flow-forecasting module of the Vista DSS software and its application to flow forecasting for 16 basins within Nova Scotia Power's hydroelectric system. Among the tasks performed by the software are collection and treatment of data (in real time) regarding meteorological forecasts, reviews and monitoring of hydro-meteorological data, updating of the state variables in the module, and the review and adjustment of sub-watershed forecasts

Hydro-economic assessment of hydrological forecasting systems

Science.gov (United States)

Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

2012-01-01

SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

Use of bias correction techniques to improve seasonal forecasts for reservoirs - A case-study in northwestern Mediterranean.

Science.gov (United States)

Marcos, Raül; Llasat, Ma Carmen; Quintana-Seguí, Pere; Turco, Marco

2018-01-01

In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter. Copyright © 2017 Elsevier B.V. All rights reserved.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

Directory of Open Access Journals (Sweden)

Jun-He Yang

2017-01-01

Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

Modeling the wind-fields of accidental releases with an operational regional forecast model

International Nuclear Information System (INIS)

Albritton, J.R.; Lee, R.L.; Sugiyama, G.

1995-01-01

The Atmospheric Release Advisory Capability (ARAC) is an operational emergency preparedness and response organization supported primarily by the Departments of Energy and Defense. ARAC can provide real-time assessments of atmospheric releases of radioactive materials at any location in the world. ARAC uses robust three-dimensional atmospheric transport and dispersion models, extensive geophysical and dose-factor databases, meteorological data-acquisition systems, and an experienced staff. Although it was originally conceived and developed as an emergency response and assessment service for nuclear accidents, the ARAC system has been adapted to also simulate non-radiological hazardous releases. For example, in 1991 ARAC responded to three major events: the oil fires in Kuwait, the eruption of Mt. Pinatubo in the Philippines, and the herbicide spill into the upper Sacramento River in California. ARAC's operational simulation system, includes two three-dimensional finite-difference models: a diagnostic wind-field scheme, and a Lagrangian particle-in-cell transport and dispersion scheme. The meteorological component of ARAC's real-time response system employs models using real-time data from all available stations near the accident site to generate a wind-field for input to the transport and dispersion model. Here we report on simulation studies of past and potential release sites to show that even in the absence of local meteorological observational data, readily available gridded analysis and forecast data and a prognostic model, the Navy Operational Regional Atmospheric Prediction System, applied at an appropriate grid resolution can successfully simulate complex local flows

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

Science.gov (United States)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

either an intermediate forecast between the extremes of the ensemble spread or a manually selected forecast based on a meteorologists advice. 2. Downstream catchments with low influence of weather forecast In downstream catchments with strong human impact on discharge (e.g. by reservoir operation) and large influence of upstream gauge observation quality on forecast quality, the 'overall error' may in most cases be larger than the combination of the 'model error' and an ensemble spread. Therefore, the overall forecast uncertainty bounds are calculated differently: a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. Here, additionally the corresponding inflow hydrograph from all upstream catchments must be used. b) As for an upstream catchment, the uncertainty range is determined by combination of 'model error' and the ensemble member forecasts c) In addition, the 'overall error' is superimposed on the 'lead forecast'. For reasons of consistency, the lead forecast must be based on the same meteorological forecast in the downstream and all upstream catchments. d) From the resulting two uncertainty ranges (one from the ensemble forecast and 'model error', one from the 'lead forecast' and 'overall error'), the envelope is taken as the most prudent uncertainty range. In sum, the uncertainty associated with each forecast run is calculated and communicated to the public in the form of 10% and 90% percentiles. As in part I of this study, the methodology as well as the useful- or uselessness of the resulting uncertainty ranges will be presented and discussed by typical examples.

Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input

DEFF Research Database (Denmark)

Wied Pedersen, Jonas; Lund, Nadia Schou Vorndran; Borup, Morten

2016-01-01

High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper...... period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior...

Physics-based forecasting of induced seismicity at Groningen gas field, the Netherlands

Science.gov (United States)

Dempsey, David; Suckale, Jenny

2017-08-01

Earthquakes induced by natural gas extraction from the Groningen reservoir, the Netherlands, put local communities at risk. Responsible operation of a reservoir whose gas reserves are of strategic importance to the country requires understanding of the link between extraction and earthquakes. We synthesize observations and a model for Groningen seismicity to produce forecasts for felt seismicity (M > 2.5) in the period February 2017 to 2024. Our model accounts for poroelastic earthquake triggering and rupture on the 325 largest reservoir faults, using an ensemble approach to model unknown heterogeneity and replicate earthquake statistics. We calculate probability distributions for key model parameters using a Bayesian method that incorporates the earthquake observations with a nonhomogeneous Poisson process. Our analysis indicates that the Groningen reservoir was not critically stressed prior to the start of production. Epistemic uncertainty and aleatoric uncertainty are incorporated into forecasts for three different future extraction scenarios. The largest expected earthquake was similar for all scenarios, with a 5% likelihood of exceeding M 4.0.

A Step Forward to Closing the Loop between Static and Dynamic Reservoir Modeling

Directory of Open Access Journals (Sweden)

Cancelliere M.

2014-12-01

Full Text Available The current trend for history matching is to find multiple calibrated models instead of a single set of model parameters that match the historical data. The advantage of several current workflows involving assisted history matching techniques, particularly those based on heuristic optimizers or direct search, is that they lead to a number of calibrated models that partially address the problem of the non-uniqueness of the solutions. The importance of achieving multiple solutions is that calibrated models can be used for a true quantification of the uncertainty affecting the production forecasts, which represent the basis for technical and economic risk analysis. In this paper, the importance of incorporating the geological uncertainties in a reservoir study is demonstrated. A workflow, which includes the analysis of the uncertainty associated with the facies distribution for a fluvial depositional environment in the calibration of the numerical dynamic models and, consequently, in the production forecast, is presented. The first step in the workflow was to generate a set of facies realizations starting from different conceptual models. After facies modeling, the petrophysical properties were assigned to the simulation domains. Then, each facies realization was calibrated separately by varying permeability and porosity fields. Data assimilation techniques were used to calibrate the models in a reasonable span of time. Results showed that even the adoption of a conceptual model for facies distribution clearly representative of the reservoir internal geometry might not guarantee reliable results in terms of production forecast. Furthermore, results also showed that realizations which seem fully acceptable after calibration were not representative of the true reservoir internal configuration and provided wrong production forecasts; conversely, realizations which did not show a good fit of the production data could reliably predict the reservoir

Appraisal of transport and deformation in shale reservoirs using natural noble gas tracers

Energy Technology Data Exchange (ETDEWEB)

Heath, Jason E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kuhlman, Kristopher L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Robinson, David G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauer, Stephen J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gardner, William Payton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of Montana, Missoula, MT (United States)

2015-09-01

This report presents efforts to develop the use of in situ naturally-occurring noble gas tracers to evaluate transport mechanisms and deformation in shale hydrocarbon reservoirs. Noble gases are promising as shale reservoir diagnostic tools due to their sensitivity of transport to: shale pore structure; phase partitioning between groundwater, liquid, and gaseous hydrocarbons; and deformation from hydraulic fracturing. Approximately 1.5-year time-series of wellhead fluid samples were collected from two hydraulically-fractured wells. The noble gas compositions and isotopes suggest a strong signature of atmospheric contribution to the noble gases that mix with deep, old reservoir fluids. Complex mixing and transport of fracturing fluid and reservoir fluids occurs during production. Real-time laboratory measurements were performed on triaxially-deforming shale samples to link deformation behavior, transport, and gas tracer signatures. Finally, we present improved methods for production forecasts that borrow statistical strength from production data of nearby wells to reduce uncertainty in the forecasts.

Multi Data Reservoir History Matching using the Ensemble Kalman Filter

KAUST Repository

Katterbauer, Klemens

2015-01-01

Reservoir history matching is becoming increasingly important with the growing demand for higher quality formation characterization and forecasting and the increased complexity and expenses for modern hydrocarbon exploration projects. History

ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

DEFF Research Database (Denmark)

Mikkelsen, Torben; Galmarini, S.; Bianconi, R.

2003-01-01

ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion...... emergency and meteorological forecasting centres, which may choose to integrate them directly intooperational emergency information systems, or possibly use them as a basis for future system development.......ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion....... ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidentalatmospheric release of radioactive material. A series of new decision-making “ENSEMBLE” procedures...

Mrica Reservoir Sedimentation: Current Situation and Future Necessary Management

Directory of Open Access Journals (Sweden)

Puji Utomo

2017-09-01

Full Text Available Mrica Reservoir is one of many reservoirs located in Central Java that experienced a considerably high sedimentation during the last ten years. This condition has caused a rapid decrease in reservoir capacity. Various countermeasures have been introduced to reduce the rate of the reservoir sedimentation through catchment management and reservoir operation by means of flushing and/or dredging. However, the sedimentation remains intensive so that the fulfillment of water demand for electrical power generation was seriously affected. This paper presents the results of evaluation on the dynamics of the purpose of this research is to evaluate the sediment balance of the Mrica Reservoir based on two different scenarios, i.e. the existing condition and another certain type of reservoir management. The study on sediment balance was carried out by estimating the sediment inflow applying sheet erosion method in combination with the analysis of sediment rating curve. The measurement of the deposited sediment rate in the reservoir was conducted through the periodic echo sounding, whereas identification of the number of sediment that has been released from the reservoir was carried out through the observation on both flushing and dredging activities. The results show that during the last decade, the rate of the sediment inflow was approximately 5.869 MCM/year, whereas the released sediment from the reservoir was 4.097 MCM/year. In order to maintain the reservoir capacity, therefore, at least 1.772 MCM/year should be released from the reservoir by means of either flushing or dredging. Sedimentation management may prolong the reservoir’s service life to exceed the design life. Without sediment management, the lifetime of the reservoir would have finished by 2016, whereas with the proper management the lifetime may be extended to 2025.

Forecasting contaminant concentrations: Spills in the White Oak Creek Basin

International Nuclear Information System (INIS)

Borders, D.M.; Hyndman, D.W.; Huff, D.D.

1987-01-01

The Streamflow Synthesis and Reservoir Regulation (SSARR) model has been installed and sufficiently calibrated for use in managing accidental release of contaminants in surface waters of the White Oak Creek (WOC) watershed at ORNL. The model employs existing watershed conditions, hydrologic parameters representing basin response to precipitation, and a Quantitative Precipitation Forecast (QPF) to predict variable flow conditions throughout the basin. Natural runoff from each of the hydrologically distinct subbasins is simulated and added to specified plant and process water discharges. The resulting flows are then routed through stream reaches and eventually to White Oak Lake (WOL), which is the outlet from the WOC drainage basin. In addition, the SSARR model is being used to simulate change in storage volumes and pool levels in WOL, and most recently, routing characteristics of contaminant spills through WOC and WOL. 10 figs

Pollutant forecasting error based on persistence of wind direction

International Nuclear Information System (INIS)

Cooper, R.E.

1978-01-01

The purpose of this report is to provide a means of estimating the reliability of forecasts of downwind pollutant concentrations from atmospheric puff releases. These forecasts are based on assuming the persistence of wind direction as determined at the time of release. This initial forecast will be used to deploy survey teams, to predict population centers that may be affected, and to estimate the amount of time available for emergency response. Reliability of forecasting is evaluated by developing a cumulative probability distribution of error as a function of lapsed time following an assumed release. The cumulative error is determined by comparing the forecast pollutant concentration with the concentration measured by sampling along the real-time meteorological trajectory. It may be concluded that the assumption of meteorological persistence for emergency response is not very good for periods longer than 3 hours. Even within this period, the possibiity for large error exists due to wind direction shifts. These shifts could affect population areas totally different from those areas first indicated

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

Science.gov (United States)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

Enhanced heavy oil recovery for carbonate reservoirs integrating cross-well seismic–a synthetic Wafra case study

KAUST Repository

Katterbauer, Klemens

2015-07-14

Heavy oil recovery has been a major focus in the oil and gas industry to counter the rapid depletion of conventional reservoirs. Various techniques for enhancing the recovery of heavy oil were developed and pilot-tested, with steam drive techniques proven in most circumstances to be successful and economically viable. The Wafra field in Saudi Arabia is at the forefront of utilizing steam recovery for carbonate heavy oil reservoirs in the Middle East. With growing injection volumes, tracking the steam evolution within the reservoir and characterizing the formation, especially in terms of its porosity and permeability heterogeneity, are key objectives for sound economic decisions and enhanced production forecasts. We have developed an integrated reservoir history matching framework using ensemble based techniques incorporating seismic data for enhancing reservoir characterization and improving history matches. Examining the performance on a synthetic field study of the Wafra field, we could demonstrate the improved characterization of the reservoir formation, determining more accurately the position of the steam chambers and obtaining more reliable forecasts of the reservoir’s recovery potential. History matching results are fairly robust even for noise levels up to 30%. The results demonstrate the potential of the integration of full-waveform seismic data for steam drive reservoir characterization and increased recovery efficiency.

Forecasting oilfield economic performance

International Nuclear Information System (INIS)

Bradley, M.E.; Wood, A.R.O.

1994-01-01

This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended

A Drought Early Warning System Using System Dynamics Model and Seasonal Climate Forecasts: a case study in Hsinchu, Taiwan.

Science.gov (United States)

Tien, Yu-Chuan; Tung, Ching-Ping; Liu, Tzu-Ming; Lin, Chia-Yu

2016-04-01

In the last twenty years, Hsinchu, a county of Taiwan, has experienced a tremendous growth in water demand due to the development of Hsinchu Science Park. In order to fulfill the water demand, the government has built the new reservoir, Baoshan second reservoir. However, short term droughts still happen. One of the reasons is that the water level of the reservoirs in Hsinchu cannot be reasonably forecasted, which sometimes even underestimates the severity of drought. The purpose of this study is to build a drought early warning system that projects the water levels of two important reservoirs, Baoshan and Baoshan second reservoir, and also the spatial distribution of water shortagewith the lead time of three months. Furthermore, this study also attempts to assist the government to improve water resources management. Hence, a system dynamics model of Touchien River, which is the most important river for public water supply in Hsinchu, is developed. The model consists of several important subsystems, including two reservoirs, water treatment plants and agricultural irrigation districts. Using the upstream flow generated by seasonal weather forecasting data, the model is able to simulate the storage of the two reservoirs and the distribution of water shortage. Moreover, the model can also provide the information under certain emergency scenarios, such as the accident or failure of a water treatment plant. At last, the performance of the proposed method and the original water resource management method that the government used were also compared. Keyword: Water Resource Management, Hydrology, Seasonal Climate Forecast, Reservoir, Early Warning, Drought

Sensitivity Analysis of Flow and Temperature Distributions of Density Currents in a River-Reservoir System under Upstream Releases with Different Durations

Directory of Open Access Journals (Sweden)

Gang Chen

2015-11-01

Full Text Available A calibrated three-dimensional Environmental Fluid Dynamics Code model was applied to simulate unsteady flow patterns and temperature distributions in the Bankhead river-reservoir system in Alabama, USA. A series of sensitivity model runs were performed under daily repeated large releases (DRLRs with different durations (2, 4 and 6 h from Smith Dam Tailrace (SDT when other model input variables were kept unchanged. The density currents in the river-reservoir system form at different reaches, are destroyed at upstream locations due to the flow momentum of the releases, and form again due to solar heating. DRLRs (140 m3/s with longer durations push the bottom cold water further downstream and maintain a cooler bottom water temperature. For the 6-h DRLR, the momentum effect definitely reaches Cordova (~43.7 km from SDT. Positive bottom velocity (density currents moving downstream is achieved 48.4%, 69.0% and 91.1% of the time with an average velocity of 0.017, 0.042 and 0.053 m/s at Cordova for the 2-h, 4-h and 6-h DRLR, respectively. Results show that DRLRs lasting for at least 4 h maintain lower water temperatures at Cordova. When the 4-h and 6-h DRLRs repeat for more than 6 and 10 days, respectively, bottom temperatures at Cordova become lower than those for the constant small release (2.83 m3/s. These large releases overwhelm the mixing effects due to inflow momentum and maintain temperature stratification at Cordova.

Robustness of a multiple-use reservoir to seasonal runoff shifts associated with climate change

International Nuclear Information System (INIS)

Lettenmaier, D.P.; Brettman, K.L.

1990-05-01

Although much remains to be learned about long-term climate change associated with anthropogenic increases in concentrations of the so-called ''greenhouse gases,'' such as carbon dioxide and methane, there is a general consensus that some global warming will result from past and present emissions. In the western United States, the dominant hydrologic effect of such warming, aside from any accompanying changes in precipitation, would be to reduce winter snow accumulations in mountainous headwaters regions. To assess the robustness of reservoir operation to such shifts in seasonal runoff, simulations were developed of monthly runoff for the American River, Washington, using the National Weather Service River Forecast System. The American River is presently unregulated; however, we tested the performance of hypothetical reservoirs with capacity of 0.25 and 0.50 of the mean annual flow for a range of annual temperature changes from 0.0 (present climate) to 4.0 degree C. We considered a multiple-purpose reservoir system operated for water supply ad hydropower, with minimum releases required for fisheries enhancement. In addition to evaluating the sensitivity of water supply, low flow, and hydropower performance using a heuristic operating rule, the relative performance of the system under present and altered climates was evaluated using an optimization algorithm, extended linear quadratic Gaussian control. This paper reports the results of hydrologic simulations for the American River, Washington. 13 refs., 8 figs

Supporting Crop Loss Insurance Policy of Indonesia through Rice Yield Modelling and Forecasting

Science.gov (United States)

van Verseveld, Willem; Weerts, Albrecht; Trambauer, Patricia; de Vries, Sander; Conijn, Sjaak; van Valkengoed, Eric; Hoekman, Dirk; Grondard, Nicolas; Hengsdijk, Huib; Schrevel, Aart; Vlasbloem, Pieter; Klauser, Dominik

2017-04-01

The Government of Indonesia has decided on a crop insurance policy to assist Indonesia's farmers and to boost food security. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform implemented in the Delft-FEWS forecasting system (Werner et al., 2013). The integrated platform brings together remote sensed data (both visible and radar) and hydrologic, crop and reservoir modelling and forecasting to improve the modelling and forecasting of rice yield. The hydrological model (wflow_sbm), crop model (wflow_lintul) and reservoir models (RTC-Tools) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in the integrated platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the G4INDO project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010.

Hydrodynamics and Water Quality forecasting over a Cloud Computing environment: INDIGO-DataCloud

Science.gov (United States)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; García, Daniel; Monteoliva, Agustín

2017-04-01

Algae Bloom due to eutrophication is an extended problem for water reservoirs and lakes that impacts directly in water quality. It can create a dead zone that lacks enough oxygen to support life and it can also be human harmful, so it must be controlled in water masses for supplying, bathing or other uses. Hydrodynamic and Water Quality modelling can contribute to forecast the status of the water system in order to alert authorities before an algae bloom event occurs. It can be used to predict scenarios and find solutions to reduce the harmful impact of the blooms. High resolution models need to process a big amount of data using a robust enough computing infrastructure. INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is an European Commission funded project that aims at developing a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The project addresses the development of solutions for different Case Studies using different Cloud-based alternatives. In the first INDIGO software release, a set of components are ready to manage the deployment of services to perform N number of Delft3D simulations (for calibrating or scenario definition) over a Cloud Computing environment, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator, AAI (Authorization, Authentication) and OneData (Distributed Storage System). Moreover, the Future Gateway portal based on Liferay, provides an user-friendly interface where the user can configure the simulations. Due to the data approach of INDIGO, the developed solutions can contribute to manage the full data life cycle of a project, thanks to different tools to manage datasets or even metadata. Furthermore, the cloud environment contributes to provide a dynamic, scalable and easy-to-use framework for non-IT experts users. This framework is potentially capable to automatize the processing of

Numerical simulation of the environmental impact of hydraulic fracturing of tight/shale gas reservoirs on near-surface groundwater: Background, base cases, shallow reservoirs, short-term gas, and water transport

Science.gov (United States)

Reagan, Matthew T; Moridis, George J; Keen, Noel D; Johnson, Jeffrey N

2015-01-01

Hydrocarbon production from unconventional resources and the use of reservoir stimulation techniques, such as hydraulic fracturing, has grown explosively over the last decade. However, concerns have arisen that reservoir stimulation creates significant environmental threats through the creation of permeable pathways connecting the stimulated reservoir with shallower freshwater aquifers, thus resulting in the contamination of potable groundwater by escaping hydrocarbons or other reservoir fluids. This study investigates, by numerical simulation, gas and water transport between a shallow tight-gas reservoir and a shallower overlying freshwater aquifer following hydraulic fracturing operations, if such a connecting pathway has been created. We focus on two general failure scenarios: (1) communication between the reservoir and aquifer via a connecting fracture or fault and (2) communication via a deteriorated, preexisting nearby well. We conclude that the key factors driving short-term transport of gas include high permeability for the connecting pathway and the overall volume of the connecting feature. Production from the reservoir is likely to mitigate release through reduction of available free gas and lowering of reservoir pressure, and not producing may increase the potential for release. We also find that hydrostatic tight-gas reservoirs are unlikely to act as a continuing source of migrating gas, as gas contained within the newly formed hydraulic fracture is the primary source for potential contamination. Such incidents of gas escape are likely to be limited in duration and scope for hydrostatic reservoirs. Reliable field and laboratory data must be acquired to constrain the factors and determine the likelihood of these outcomes. Key Points: Short-term leakage fractured reservoirs requires high-permeability pathways Production strategy affects the likelihood and magnitude of gas release Gas release is likely short-term, without additional driving forces PMID

Developing Novel Reservoir Rule Curves Using Seasonal Inflow Projections

Science.gov (United States)

Tseng, Hsin-yi; Tung, Ching-pin

2015-04-01

Due to significant seasonal rainfall variations, reservoirs and their flexible operational rules are indispensable to Taiwan. Furthermore, with the intensifying impacts of climate change on extreme climate, the frequency of droughts in Taiwan has been increasing in recent years. Drought is a creeping phenomenon, the slow onset character of drought makes it difficult to detect at an early stage, and causes delays on making the best decision of allocating water. For these reasons, novel reservoir rule curves using projected seasonal streamflow are proposed in this study, which can potentially reduce the adverse effects of drought. This study dedicated establishing new rule curves which consider both current available storage and anticipated monthly inflows with leading time of two months to reduce the risk of water shortage. The monthly inflows are projected based on the seasonal climate forecasts from Central Weather Bureau (CWB), which a weather generation model is used to produce daily weather data for the hydrological component of the GWLF. To incorporate future monthly inflow projections into rule curves, this study designs a decision flow index which is a linear combination of current available storage and inflow projections with leading time of 2 months. By optimizing linear relationship coefficients of decision flow index, the shape of rule curves and the percent of water supply in each zone, the best rule curves to decrease water shortage risk and impacts can be developed. The Shimen Reservoir in the northern Taiwan is used as a case study to demonstrate the proposed method. Existing rule curves (M5 curves) of Shimen Reservoir are compared with two cases of new rule curves, including hindcast simulations and historic seasonal forecasts. The results show new rule curves can decrease the total water shortage ratio, and in addition, it can also allocate shortage amount to preceding months to avoid extreme shortage events. Even though some uncertainties in

Modelling of Reservoir Operations using Fuzzy Logic and ANNs

Science.gov (United States)

Van De Giesen, N.; Coerver, B.; Rutten, M.

2015-12-01

Today, almost 40.000 large reservoirs, containing approximately 6.000 km3 of water and inundating an area of almost 400.000 km2, can be found on earth. Since these reservoirs have a storage capacity of almost one-sixth of the global annual river discharge they have a large impact on the timing, volume and peaks of river discharges. Global Hydrological Models (GHM) are thus significantly influenced by these anthropogenic changes in river flows. We developed a parametrically parsimonious method to extract operational rules based on historical reservoir storage and inflow time-series. Managing a reservoir is an imprecise and vague undertaking. Operators always face uncertainties about inflows, evaporation, seepage losses and various water demands to be met. They often base their decisions on experience and on available information, like reservoir storage and the previous periods inflow. We modeled this decision-making process through a combination of fuzzy logic and artificial neural networks in an Adaptive-Network-based Fuzzy Inference System (ANFIS). In a sensitivity analysis, we compared results for reservoirs in Vietnam, Central Asia and the USA. ANFIS can indeed capture reservoirs operations adequately when fed with a historical monthly time-series of inflows and storage. It was shown that using ANFIS, operational rules of existing reservoirs can be derived without much prior knowledge about the reservoirs. Their validity was tested by comparing actual and simulated releases with each other. For the eleven reservoirs modelled, the normalised outflow, , was predicted with a MSE of 0.002 to 0.044. The rules can be incorporated into GHMs. After a network for a specific reservoir has been trained, the inflow calculated by the hydrological model can be combined with the release and initial storage to calculate the storage for the next time-step using a mass balance. Subsequently, the release can be predicted one time-step ahead using the inflow and storage.

Communicating uncertainty in hydrological forecasts: mission impossible?

Science.gov (United States)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted

Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition.

Science.gov (United States)

Wang, Wen-chuan; Chau, Kwok-wing; Qiu, Lin; Chen, Yang-bo

2015-05-01

Hydrological time series forecasting is one of the most important applications in modern hydrology, especially for the effective reservoir management. In this research, an artificial neural network (ANN) model coupled with the ensemble empirical mode decomposition (EEMD) is presented for forecasting medium and long-term runoff time series. First, the original runoff time series is decomposed into a finite and often small number of intrinsic mode functions (IMFs) and a residual series using EEMD technique for attaining deeper insight into the data characteristics. Then all IMF components and residue are predicted, respectively, through appropriate ANN models. Finally, the forecasted results of the modeled IMFs and residual series are summed to formulate an ensemble forecast for the original annual runoff series. Two annual reservoir runoff time series from Biuliuhe and Mopanshan in China, are investigated using the developed model based on four performance evaluation measures (RMSE, MAPE, R and NSEC). The results obtained in this work indicate that EEMD can effectively enhance forecasting accuracy and the proposed EEMD-ANN model can attain significant improvement over ANN approach in medium and long-term runoff time series forecasting. Copyright © 2015 Elsevier Inc. All rights reserved.

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

Science.gov (United States)

Barghouty, Nasser; Falconer, David

2015-01-01

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Sediment pollution characteristics and in situ control in a deep drinking water reservoir.

Science.gov (United States)

Zhou, Zizhen; Huang, Tinglin; Li, Yang; Ma, Weixing; Zhou, Shilei; Long, Shenghai

2017-02-01

Sediment pollution characteristics, in situ sediment release potential, and in situ inhibition of sediment release were investigated in a drinking water reservoir. Results showed that organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) in sediments increased from the reservoir mouth to the main reservoir. Fraction analysis indicated that nitrogen in ion exchangeable form and NaOH-extractable P (Fe/Al-P) accounted for 43% and 26% of TN and TP in sediments of the main reservoir. The Risk Assessment Code for metal elements showed that Fe and Mn posed high to very high risk. The results of the in situ reactor experiment in the main reservoir showed the same trends as those observed in the natural state of the reservoir in 2011 and 2012; the maximum concentrations of total OC, TN, TP, Fe, and Mn reached 4.42mg/L, 3.33mg/L, 0.22mg/L, 2.56mg/L, and 0.61mg/L, respectively. An in situ sediment release inhibition technology, the water-lifting aerator, was utilized in the reservoir. The results of operating the water-lifting aerator indicated that sediment release was successfully inhibited and that OC, TN, TP, Fe, and Mn in surface sediment could be reduced by 13.25%, 15.23%, 14.10%, 5.32%, and 3.94%, respectively. Copyright © 2016. Published by Elsevier B.V.

a system approach to the long term forecasting of the climat data in baikal region

Science.gov (United States)

Abasov, N.; Berezhnykh, T.

2003-04-01

that take place in the Baikal, the Bratsk and Ust-Ilimsk reservoirs: long low-water periods and sudden periods of extremely high water levels. For example, low-water periods, observed in the reservoirs of the Angara cascade can be classified under four risk categories : 1 - acceptable (negligible reduction of electric power generation by hydropower plants; certain difficulty in meeting environmental and navigation requirements); 2 - significant (substantial reduction of electric power generation by hydropower plants; certain restriction on water releases for navigation; violation of environmental requirements in some years); 3 - emergency (big losses in electric power generation; limited electricity supply to large consumers; significant restriction of water releases for navigation; threat of exposure of drinkable water intake works; violation of environmental requirements for a number of years); 4 - catastrophic (energy crisis; social crisis exposure of drinkable water intake works; termination of navigation; environmental catastrophe). Management of energy systems consists in operative, many-year regulation and perspective planning and has to take into account the analysis of operative data (water reserves in reservoirs), long-term statistics and relations among natural processes and also forecasts - short-term (for a day, week, decade), long-term and/or super-long-term (from a month to several decades). Such natural processes as water inflow to reservoirs, air temperatures during heating periods depend in turn on external factors: prevailing types of atmospheric circulation, intensity of the 11- and 22-year cycles of solar activity, volcanic activity, interaction between the ocean and atmosphere, etc. Until recently despite the formed scientific schools on long-term forecasting (I.P.Druzhinin, A.P.Reznikhov) the energy system management has been based on specially drawn dispatching schedules and long-term hydrometeorological forecasts only without attraction of

Overview of Hydrometeorologic Forecasting Procedures at BC Hydro

Science.gov (United States)

McCollor, D.

2004-12-01

Energy utility companies must balance production from limited sources with increasing demand from industrial, business, and residential consumers. The utility planning process requires a balanced, efficient, and effective distribution of energy from source to consumer. Therefore utility planners must consider the impact of weather on energy production and consumption. Hydro-electric companies should be particularly tuned to weather because their source of energy is water, and water supply depends on precipitation. BC Hydro operates as the largest hydro-electric company in western Canada, managing over 30 reservoirs within the province of British Columbia, and generating electricity for 1.6 million people. BC Hydro relies on weather forecasts of watershed precipitation and temperature to drive hydrologic reservoir inflow models and of urban temperatures to meet energy demand requirements. Operations and planning specialists in the company rely on current, value-added weather forecasts for extreme high-inflow events, daily reservoir operations planning, and long-term water resource management. Weather plays a dominant role for BC Hydro financial planners in terms of sensitive economic responses. For example, a two percent change in hydropower generation, due in large part to annual precipitation patterns, results in an annual net change of \\50 million in earnings. A five percent change in temperature produces a \\5 million change in yearly earnings. On a daily basis, significant precipitation events or temperature extremes involve potential profit/loss decisions in the tens of thousands of dollars worth of power generation. These factors are in addition to environmental and societal costs that must be considered equally as part of a triple bottom line reporting structure. BC Hydro water resource managers require improved meteorological information from recent advancements in numerical weather prediction. At BC Hydro, methods of providing meteorological forecast data

Hydrological Analysis for Inflow Forecasting into Temengor Dam

Science.gov (United States)

Najid, MI; Sidek, LM; Hidayah, B.; Roseli, ZA

2016-03-01

These days, natural disaster such as flood is the main concern for hydrologists. One of solutions in understanding the reason of flood is by prediction of the event sooner than normal occurrence. One of the criteria is lead time or travel time that is important in the study of fresh waters and flood events. Therefore, estimation of lead or travel time for flood event can be beneficial primary information. The objective of this study is to estimate the lead time or travel time for outlet of Temengor dam in Malaysia. Tenaga Nasional Berhad (TNB) Sungai Perak dam operation has the main contribution on decision support for early water released and flood warning to authorities and locals resident for in the down streams area. For this study, hydrological analysis carried out will help to determine which years that give more rainfall contribution into the reservoir. Rainfall contribution of reservoir help to understanding rainfall distribution and peak discharge on that period. It also help for calibration of forecasting model system for better accuracy of flood hydrograph. There may be various methods to determine the rainfall contribution of catchment. The result has shown that, the rainfall contribution for Temengor catchment, is more on November in each year which is the monsoon season in Malaysia. TNB dam operational decision support systems can prepare and be more aware at this time for flood control and flood mitigation.

Real-time management of a multipurpose water reservoir with a heteroscedastic inflow model

Science.gov (United States)

Pianosi, F.; Soncini-Sessa, R.

2009-10-01

Stochastic dynamic programming has been extensively used as a method for designing optimal regulation policies for water reservoirs. However, the potential of this method is dramatically reduced by its computational burden, which often forces to introduce strong approximations in the model of the system, especially in the description of the reservoir inflow. In this paper, an approach to partially remedy this problem is proposed and applied to a real world case study. It foresees solving the management problem on-line, using a reduced model of the system and the inflow forecast provided by a dynamic model. By doing so, all the hydrometeorological information that is available in real-time is fully exploited. The model here proposed for the inflow forecasting is a nonlinear, heteroscedastic model that provides both the expected value and the standard deviation of the inflow through dynamic relations. The effectiveness of such model for the purpose of the reservoir regulation is evaluated through simulation and comparison with the results provided by conventional homoscedastic inflow models.

Simulation of Reservoir Sediment Flushing of the Three Gorges Reservoir Using an Artificial Neural Network

Directory of Open Access Journals (Sweden)

Xueying Li

2016-05-01

Full Text Available Reservoir sedimentation and its effect on the environment are the most serious world-wide problems in water resources development and utilization today. As one of the largest water conservancy projects, the Three Gorges Reservoir (TGR has been controversial since its demonstration period, and sedimentation is the major concern. Due to the complex physical mechanisms of water and sediment transport, this study adopts the Error Back Propagation Training Artificial Neural Network (BP-ANN to analyze the relationship between the sediment flushing efficiency of the TGR and its influencing factors. The factors are determined by the analysis on 1D unsteady flow and sediment mathematical model, mainly including reservoir inflow, incoming sediment concentration, reservoir water level, and reservoir release. Considering the distinguishing features of reservoir sediment delivery in different seasons, the monthly average data from 2003, when the TGR was put into operation, to 2011 are used to train, validate, and test the BP-ANN model. The results indicate that, although the sample space is quite limited, the whole sediment delivery process can be schematized by the established BP-ANN model, which can be used to help sediment flushing and thus decrease the reservoir sedimentation.

Real-time optimisation of the Hoa Binh reservoir, Vietnam

DEFF Research Database (Denmark)

Richaud, Bertrand; Madsen, Henrik; Rosbjerg, Dan

2011-01-01

-time optimisation. First, the simulation-optimisation framework is applied for optimising reservoir operating rules. Secondly, real-time and forecast information is used for on-line optimisation that focuses on short-term goals, such as flood control or hydropower generation, without compromising the deviation...... in the downstream part of the Red River, and at the same time to increase hydropower generation and to save water for the dry season. The real-time optimisation procedure further improves the efficiency of the reservoir operation and enhances the flexibility for the decision-making. Finally, the quality......Multi-purpose reservoirs often have to be managed according to conflicting objectives, which requires efficient tools for trading-off the objectives. This paper proposes a multi-objective simulation-optimisation approach that couples off-line rule curve optimisation with on-line real...

Development of infill drilling recovery models for carbonates reservoirs using neural networks and multivariate statistical as a novel method

International Nuclear Information System (INIS)

Soto, R; Wu, Ch. H; Bubela, A M

1999-01-01

This work introduces a novel methodology to improve reservoir characterization models. In this methodology we integrated multivariate statistical analyses, and neural network models for forecasting the infill drilling ultimate oil recovery from reservoirs in San Andres and Clearfork carbonate formations in west Texas. Development of the oil recovery forecast models help us to understand the relative importance of dominant reservoir characteristics and operational variables, reproduce recoveries for units included in the database, forecast recoveries for possible new units in similar geological setting, and make operational (infill drilling) decisions. The variety of applications demands the creation of multiple recovery forecast models. We have developed intelligent software (Soto, 1998), oilfield intelligence (01), as an engineering tool to improve the characterization of oil and gas reservoirs. 01 integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphic design, and inference engine modules. One of the challenges in this research was to identify the dominant and the optimum number of independent variables. The variables include porosity, permeability, water saturation, depth, area, net thickness, gross thickness, formation volume factor, pressure, viscosity, API gravity, number of wells in initial water flooding, number of wells for primary recovery, number of infill wells over the initial water flooding, PRUR, IWUR, and IDUR. Multivariate principal component analysis is used to identify the dominant and the optimum number of independent variables. We compared the results from neural network models with the non-parametric approach. The advantage of the non-parametric regression is that it is easy to use. The disadvantage is that it retains a large variance of forecast results for a particular data set. We also used neural network concepts to develop recovery

ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

Energy Technology Data Exchange (ETDEWEB)

Mikkelsen, T; Galmarini, S; Bianconi, R; French, S [eds.

2003-11-01

ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

Energy Technology Data Exchange (ETDEWEB)

Mikkelsen, T.; Galmarini, S.; Bianconi, R.; French, S. (eds.)

2003-11-01

ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

Optimisation of decision making under uncertainty throughout field lifetime: A fractured reservoir example

Science.gov (United States)

Arnold, Dan; Demyanov, Vasily; Christie, Mike; Bakay, Alexander; Gopa, Konstantin

2016-10-01

Assessing the change in uncertainty in reservoir production forecasts over field lifetime is rarely undertaken because of the complexity of joining together the individual workflows. This becomes particularly important in complex fields such as naturally fractured reservoirs. The impact of this problem has been identified in previous and many solutions have been proposed but never implemented on complex reservoir problems due to the computational cost of quantifying uncertainty and optimising the reservoir development, specifically knowing how many and what kind of simulations to run. This paper demonstrates a workflow that propagates uncertainty throughout field lifetime, and into the decision making process by a combination of a metric-based approach, multi-objective optimisation and Bayesian estimation of uncertainty. The workflow propagates uncertainty estimates from appraisal into initial development optimisation, then updates uncertainty through history matching and finally propagates it into late-life optimisation. The combination of techniques applied, namely the metric approach and multi-objective optimisation, help evaluate development options under uncertainty. This was achieved with a significantly reduced number of flow simulations, such that the combined workflow is computationally feasible to run for a real-field problem. This workflow is applied to two synthetic naturally fractured reservoir (NFR) case studies in appraisal, field development, history matching and mid-life EOR stages. The first is a simple sector model, while the second is a more complex full field example based on a real life analogue. This study infers geological uncertainty from an ensemble of models that are based on the carbonate Brazilian outcrop which are propagated through the field lifetime, before and after the start of production, with the inclusion of production data significantly collapsing the spread of P10-P90 in reservoir forecasts. The workflow links uncertainty

Lava lake level as a gauge of magma reservoir pressure and eruptive hazard

Science.gov (United States)

Patrick, Matthew R.; Anderson, Kyle R.; Poland, Michael P.; Orr, Tim R.; Swanson, Donald A.

2015-01-01

Forecasting volcanic activity relies fundamentally on tracking magma pressure through the use of proxies, such as ground surface deformation and earthquake rates. Lava lakes at open-vent basaltic volcanoes provide a window into the uppermost magma system for gauging reservoir pressure changes more directly. At Kīlauea Volcano (Hawaiʻi, USA) the surface height of the summit lava lake in Halemaʻumaʻu Crater fluctuates with surface deformation over short (hours to days) and long (weeks to months) time scales. This correlation implies that the lake behaves as a simple piezometer of the subsurface magma reservoir. Changes in lava level and summit deformation scale with (and shortly precede) changes in eruption rate from Kīlauea's East Rift Zone, indicating that summit lava level can be used for short-term forecasting of rift zone activity and associated hazards at Kīlauea.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

Science.gov (United States)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality

Study of the copepods population in the Oum Er Rbia estuary (Atlantic Moroccan coast): tides and reservoir release effects

International Nuclear Information System (INIS)

El Khalki, A.; Moncef, M.

2007-01-01

Variation of environmental parameters and copepods population were studied in the Oum Er Rbia estuary (Atlantic - Moroccan coast) according to the seasons, ( August 1995 to August 1997), tides and reservoir release events. Environemental variability influences copepods diversity and abundance. Salinity (5 to 20 g l-1) appears as the main controlling factor. Among the 27 copepod species recorded, only three marine species (Oithona helgolandica, Euterpina acutifrons, Acartia clausi) and one freshwater species (Acanthocyclops robustus) are able to maintain significant populations due to their large degree of tolerance to salinity changes. (author)

Applicability of WRF-Lake System in Studying Reservoir-Induced Impacts on Local Climate: Case Study of Two Reservoirs with Contrasting Characteristics

Science.gov (United States)

Wang, F.; Zhu, D.; Ni, G.; Sun, T.

2017-12-01

Large reservoirs play a key role in regional hydrological cycles as well as in modulating the local climate. The emerging large reservoirs in concomitant with rapid hydropower exploitation in southwestern China warrant better understanding of their impacts on local and regional climates. One of the crucial pathways through which reservoirs impact the climate is lake-atmospheric interaction. Although such interactions have been widely studied with numeric weather prediction (NWP) models, an outstanding limitation across various NWPs resides on the poor thermodynamic representation of lakes. The recent version of Weather Research and Forecasting (WRF) system has been equipped with a one-dimensional lake model to better represent the thermodynamics of large water body and has been shown to enhance the its predication skill in the lake-atmospheric interaction. In this study, we further explore the applicability of the WRF-Lake system in two reservoirs with contrasting characteristics: Miyun Reservoir with an average depth of 30 meters in North China Plain, and Nuozhadu Reservoir with an average depth of 200 meters in the Tibetan Plateau Region. Driven by the high spatiotemporal resolution meteorological forcing data, the WRF-Lake system is used to simulate the water temperature and surface energy budgets of the two reservoirs after the evaluation against temperature observations. The simulated results show the WRF-Lake model can well predict the vertical profile of water temperature in Miyun Reservoir, but underestimates deep water temperature and overestimates surface temperature in the deeper Nuozhadu Reservoir. In addition, sensitivity analysis indicates the poor performance of the WRF-Lake system in Nuozhadu Reservoir could be attributed to the weak vertical mixing in the model, which can be improved by tuning the eddy diffusion coefficient ke . Keywords: reservoir-induced climatic impact; lake-atmospheric interaction; WRF-Lake system; hydropower exploitation

Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

Science.gov (United States)

Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

2015-01-01

Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

Optimal Operation of Hydropower Reservoirs under Climate Change: The Case of Tekeze Reservoir, Eastern Nile

Directory of Open Access Journals (Sweden)

Fikru Fentaw Abera

2018-03-01

Full Text Available Optimal operation of reservoirs is very essential for water resource planning and management, but it is very challenging and complicated when dealing with climate change impacts. The objective of this paper was to assess existing and future hydropower operation at the Tekeze reservoir in the face of climate change. In this study, a calibrated and validated Soil and Water Assessment Tool (SWAT was used to model runoff inflow into the Tekeze hydropower reservoir under present and future climate scenarios. Inflow to the reservoir was simulated using hydro-climatic data from an ensemble of downscaled climate data based on the Coordinated Regional climate Downscaling Experiment over African domain (CORDEX-Africa with Coupled Intercomparison Project Phase 5 (CMIP5 simulations under Representative Concentration Pathway (RCP4.5 and RCP8.5 climate scenarios. Observed and projected inflows to Tekeze hydropower reservoir were used as input to the US Army Corps of Engineer’s Reservoir Evaluation System Perspective Reservoir Model (HEC-ResPRM, a reservoir operation model, to optimize hydropower reservoir release, storage and pool level. Results indicated that climate change has a clear impact on reservoir inflow and showed increase in annual and monthly inflow into the reservoir except in dry months from May to June under RCP4.5 and RCP8.5 climate scenarios. HEC-ResPRM optimal operation results showed an increase in Tekeze reservoir power storage potential up to 25% and 30% under RCP4.5 and RCP8.5 climate scenarios, respectively. This implies that Tekeze hydropower production will be affected by climate change. This analysis can be used by water resources planners and mangers to develop reservoir operation techniques considering climate change impact to increase power production.

Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011

Science.gov (United States)

Graham, Jennifer L.; Ziegler, Andrew C.; Loving, Brian L.; Loftin, Keith A.

2012-01-01

Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds. Toxins and taste-and-odor compounds may cause substantial economic and public health concerns and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply, recreation, or aquaculture. The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Water released from Milford Lake to the Kansas River during a toxic cyanobacterial bloom in late August 2011 prompted concerns about cyanobacteria and associated toxins and taste-and-odor compounds in downstream drinking-water supplies. During September and October 2011 water-quality samples were collected to characterize the transport of cyanobacteria and associated compounds from upstream reservoirs to the Kansas River. This study is one of the first to quantitatively document the transport of cyanobacteria and associated compounds during reservoir releases and improves understanding of the fate and transport of cyanotoxins and taste-and-odor compounds downstream from reservoirs. Milford Lake was the only reservoir in the study area with an ongoing cyanobacterial bloom during reservoir releases. Concentrations of cyanobacteria and associated toxins and taste-and-odor compounds in Milford Lake (upstream from the dam) were not necessarily indicative of outflow conditions (below the dam). Total microcystin concentrations, one of the most commonly occurring cyanobacterial toxins, in Milford Lake were 650 to 7,500 times higher than the Kansas Department of Health and Environment guidance level for a public health warning (20 micrograms per liter) for most of September 2011. By comparison, total microcystin concentrations in the Milford Lake outflow generally were less than 10 percent of the concentrations in surface accumulations, and never exceeded 20 micrograms per liter. The Republican River, downstream from

Web3DGIS-Based System for Reservoir Landslide Monitoring and Early Warning

Directory of Open Access Journals (Sweden)

Huang Huang

2016-02-01

Full Text Available Landslides are the most frequent type of natural disaster, and they bring about large-scale damage and are a threat to human lives and infrastructure; therefore, the ability to conduct real-time monitoring and early warning is important. In this study, a Web3DGIS (Web3D geographic information systems system for monitoring and forecasting landslides was developed using the Danjiangkou Reservoir area as a case study. The development of this technique involved system construction, functional design, organizing and managing multi-source spatial data, and implementing a forecasting plan and landslide-forecasting model. By integrating sensor technologies, spatial information technologies, 3D visualization technologies, and a landslide-forecasting model, the results of this study provide a tool for real-time monitoring at potential landslide sites. When relevant data from these sites reach threshold values, the model automatically initiates forecasting procedures, and sends information to disaster prevention sectors for emergency management.

Oral fluoride reservoirs and the prevention of dental caries.

Science.gov (United States)

Vogel, Gerald Lee

2011-01-01

Current models for increasing the anti-caries effects of fluoride (F) agents emphasize the importance of maintaining a cariostatic concentration of F in oral fluids. The concentration of F in oral fluids is maintained by the release of this ion from bioavailable reservoirs on the teeth, oral mucosa and - most importantly, because of its association with the caries process - dental plaque. Oral F reservoirs appear to be of two types: (1) mineral reservoirs, in particular calcium fluoride or phosphate-contaminated 'calcium-fluoride-like' deposits; (2) biological reservoirs, in particular (with regard to dental plaque) F held to bacteria or bacterial fragments via calcium-fluoride bonds. The fact that all these reservoirs are mediated by calcium implies that their formation is limited by the low concentration of calcium in oral fluids. By using novel procedures which overcome this limitation, the formation of these F reservoirs after topical F application can be greatly increased. Although these increases are associated with substantive increases in salivary and plaque fluid F, and hence a potential increase in cariostatic effect, it is unclear if such changes are related to the increases in the amount of these reservoirs, or changes in the types of F deposits formed. New techniques have been developed for identifying and quantifying these deposits which should prove useful in developing agents that enhance formation of oral F reservoirs with optimum F release characteristics. Such research offers the prospect of decreasing the F content of topical agents while simultaneously increasing their cariostatic effect. Copyright © 2011 S. Karger AG, Basel.

OPTIMIZATION OF INFILL DRILLING IN NATURALLY-FRACTURED TIGHT-GAS RESERVOIRS

Energy Technology Data Exchange (ETDEWEB)

Lawrence W. Teufel; Her-Yuan Chen; Thomas W. Engler; Bruce Hart

2004-05-01

A major goal of industry and the U.S. Department of Energy (DOE) fossil energy program is to increase gas reserves in tight-gas reservoirs. Infill drilling and hydraulic fracture stimulation in these reservoirs are important reservoir management strategies to increase production and reserves. Phase II of this DOE/cooperative industry project focused on optimization of infill drilling and evaluation of hydraulic fracturing in naturally-fractured tight-gas reservoirs. The cooperative project involved multidisciplinary reservoir characterization and simulation studies to determine infill well potential in the Mesaverde and Dakota sandstone formations at selected areas in the San Juan Basin of northwestern New Mexico. This work used the methodology and approach developed in Phase I. Integrated reservoir description and hydraulic fracture treatment analyses were also conducted in the Pecos Slope Abo tight-gas reservoir in southeastern New Mexico and the Lewis Shale in the San Juan Basin. This study has demonstrated a methodology to (1) describe reservoir heterogeneities and natural fracture systems, (2) determine reservoir permeability and permeability anisotropy, (3) define the elliptical drainage area and recoverable gas for existing wells, (4) determine the optimal location and number of new in-fill wells to maximize economic recovery, (5) forecast the increase in total cumulative gas production from infill drilling, and (6) evaluate hydraulic fracture simulation treatments and their impact on well drainage area and infill well potential. Industry partners during the course of this five-year project included BP, Burlington Resources, ConocoPhillips, and Williams.

Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements.

Science.gov (United States)

Straume, Anne Grete; N'dri Koffi, Ernest; Nodop, Katrin

1998-11-01

Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the meteorological input data. A Lagrangian dispersion model, the Severe Nuclear Accident Program, is used here to investigate the effect of errors in the meteorological input data due to analysis error. An ensemble forecast, produced at the European Centre for Medium-Range Weather Forecasts, is then used as model input. The ensemble forecast members are generated by perturbing the initial meteorological fields of the weather forecast. The perturbations are calculated from singular vectors meant to represent possible forecast developments generated by instabilities in the atmospheric flow during the early part of the forecast. The instabilities are generated by errors in the analyzed fields. Puff predictions from the dispersion model, using ensemble forecast input, are compared, and a large spread in the predicted puff evolutions is found. This shows that the quality of the meteorological input data is important for the success of the dispersion model. In order to evaluate the dispersion model, the calculations are compared with measurements from the European Tracer Experiment. The model manages to predict the measured puff evolution concerning shape and time of arrival to a fairly high extent, up to 60 h after the start of the release. The modeled puff is still too narrow in the advection direction.

Implications of the sedimentation phenomenon in the design of hydropower reservoirs

International Nuclear Information System (INIS)

Scvortov, Felix; Armencea, Gheorghe

1992-01-01

The influence of sedimentation phenomena on the operational parameters of the hydropower reservoirs built on several Romanian rivers was assessed. A cascade of eight reservoirs on the Olt river, with initial volumes of 20-50 M m 3 , lost about 30% of the conservation capacity and about 3-7% of head as well. Smaller reservoirs, with volumes of 2-10 M m 3 , lost 60-85% of their capacity. Dredging operations had to be done, thus, increasing the initial costs by 20%. The acquired experience revealed that the evolution in time of the reservoir capacity over the operation period should be as accurately as possible taken into account in the designing stage. The operation conditions and designing criterions for small and medium hydropower reservoir have to be reassessed also from the environmental and efficiency points of view. The content of the paper is the following: 1. Sedimentation knowledge and planning concepts for inland rivers; 2. Implications of the sedimentation phenomenon; 3. Forecast of the sedimentation phenomenon; 4. Retrospective and perspective; 5. Conclusions. (authors)

ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

OpenAIRE

Mikkelsen, Torben; Galmarini, S.; Bianconi, R.; French, S.

2003-01-01

ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an a...

Gambling scores for earthquake predictions and forecasts

Science.gov (United States)

Zhuang, Jiancang

2010-04-01

This paper presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points betted by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when the true model is a renewal process, the stress release model or the ETAS model and when the reference model is the Poisson model.

Spatial forecast of landslides in three gorges based on spatial data mining.

Science.gov (United States)

Wang, Xianmin; Niu, Ruiqing

2009-01-01

The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc). China-Brazil Earth Resources Satellite (Cbers) images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County) in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods.

EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

KAUST Repository

Katterbauer, Klemens; Hoteit, Ibrahim; Sun, Shuyu

2014-01-01

into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential

Multi-data reservoir history matching of crosswell seismic, electromagnetics and gravimetry data

KAUST Repository

Katterbauer, Klemens

2014-01-01

Reservoir engineering has become of prime importance for oil and gas field development projects. With rising complexity, reservoir simulations and history matching have become critical for fine-tuning reservoir production strategies, improved subsurface formation knowledge and forecasting remaining reserves. The sparse spatial sampling of production data has posed a significant challenge for reducing uncertainty of subsurface parameters. Seismic, electromagnetic and gravimetry techniques have found widespread application in enhancing exploration for oil and gas and monitor reservoirs, however these data have been interpreted and analyzed mostly separately rarely utilizing the synergy effects that may be attainable. With the incorporation of multiple data into the reservoir history matching process there has been the request knowing the impact each incorporated observation has on the estimation. We present multi-data ensemble-based history matching framework for the incorporation of multiple data such as seismic, electromagnetics, and gravimetry for improved reservoir history matching and provide an adjointfree ensemble sensitivity method to compute the impact of each observation on the estimated reservoir parameters. The incorporation of all data sets displays the advantages multiple data may provide for enhancing reservoir understanding and matching, with the impact of each data set on the matching improvement being determined by the ensemble sensitivity method.

Effects of reservoirs water level variations on fish recruitment

Directory of Open Access Journals (Sweden)

Fabíula T. de Lima

2017-10-01

Full Text Available ABSTRACT The construction of hydroelectric power plants has many social and environmental impacts. Among them, the impacts on fish communities, which habitats are drastically modified by dams, with consequences across the ecosystem. This study aimed to assess the influence of water level (WL variations in the reservoirs of the Itá and Machadinho hydroelectric plants on the recruitment of fish species from the upper Uruguay River in southern Brazil. The data analyzed resulted from the WL variation produced exclusively by the hydroelectric plants generation and were collected between the years 2001 and 2012. The results showed significant correlations between the abundance of juvenile fish and the hydrological parameters only for some reproductive guilds. The species that spawn in nests showed, in general, a clear preference for the stability in the WL of the reservoirs, while the species that spawn in macrophytes or that release demersal eggs showed no significant correlation between the abundance of juvenile fish and hydrological parameters. A divergence of results between the two reservoirs was observed between the species that release semi-dense eggs; a positive correlation with a more stable WL was only observed in the Machadinho reservoir. This result can be driven by a wider range of WL variation in Machadinho reservoir.

Fluid flow in gas condensate reservoirs. The interplay of forces and their relative strengths

Energy Technology Data Exchange (ETDEWEB)

Ursin, Jann-Rune [Stavanger University College, Department of Petroleum Engineering, PO Box 8002, Stavanger, 4068 (Norway)

2004-02-01

Natural production from gas condensate reservoirs is characterized by gas condensation and liquid dropout in the reservoir, first in the near wellbore volume, then as a cylindrical shaped region, dynamically developing into the reservoir volume. The effects of liquid condensation are reduced productivity and loss of production. Successful forecast of well productivity and reservoir production depends on detailed understanding of the effect of various forces acting on fluid flow in time and space. The production form gas condensate reservoirs is thus indirectly related to the interplay of fundamental forces, such as the viscosity, the capillary, the gravitational and the inertial force and their relative strengths, demonstrated by various dimensionless numbers. Dimensionless numbers are defined and calculated for all pressure and space coordinates in a test reservoir. Various regions are identified where certain forces are more important than others. Based on reservoir pressure development, liquid condensation and the numerical representation of dimensionless numbers, a conceptual understanding of a varying reservoir permeability has been reached.The material balance, the reservoir fluid flow and the wellbore flow calculations are performed on a cylindrical reservoir model. The ratios between fundamental forces are calculated and dimensionless numbers defined. The interplay of forces, demonstrated by these numbers, are calculated as function of radial dimension and reservoir pressure.

2014 Gulf of Mexico Hypoxia Forecast

Science.gov (United States)

Scavia, Donald; Evans, Mary Anne; Obenour, Dan

2014-01-01

The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 4,761 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 14,000 square kilometers (95% credible interval, 8,000 to 20,000) – an “average year”. Our forecast hypoxic volume is 50 km3 (95% credible interval, 20 to 77).

Evaluating Potential for Large Releases from CO2 Storage Reservoirs: Analogs, Scenarios, and Modeling Needs

International Nuclear Information System (INIS)

Birkholzer, Jens; Pruess, Karsten; Lewicki, Jennifer; Tsang, Chin-Fu; Karimjee, Anhar

2005-01-01

While the purpose of geologic storage of CO 2 in deep saline formations is to trap greenhouse gases underground, the potential exists for CO 2 to escape from the target reservoir, migrate upward along permeable pathways, and discharge at the land surface. Such discharge is not necessarily a serious concern, as CO 2 is a naturally abundant and relatively benign gas in low concentrations. However, there is a potential risk to health, safety and environment (HSE) in the event that large localized fluxes of CO 2 were to occur at the land surface, especially where CO 2 could accumulate. In this paper, we develop possible scenarios for large CO 2 fluxes based on the analysis of natural analogues, where large releases of gas have been observed. We are particularly interested in scenarios which could generate sudden, possibly self-enhancing, or even eruptive release events. The probability for such events may be low, but the circumstances under which they might occur and potential consequences need to be evaluated in order to design appropriate site selection and risk management strategies. Numerical modeling of hypothetical test cases is needed to determine critical conditions for such events, to evaluate whether such conditions may be possible at designated storage sites, and, if applicable, to evaluate the potential HSE impacts of such events and design appropriate mitigation strategies

Mercury and methylmercury in reservoirs in Indiana

Science.gov (United States)

Risch, Martin R.; Fredericksen, Amanda L.

2015-01-01

Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.

Modeling of Turbidity Variation in Two Reservoirs Connected by a Water Transfer Tunnel in South Korea

Directory of Open Access Journals (Sweden)

Jae Chung Park

2017-06-01

Full Text Available The Andong and Imha reservoirs in South Korea are connected by a water transfer tunnel. The turbidity of the Imha reservoir is much higher than that of the Andong reservoir. Thus, it is necessary to examine the movement of turbidity between the two reservoirs via the water transfer tunnel. The aim of this study was to investigate the effect of the water transfer tunnel on the turbidity behavior of the two connecting reservoirs and to further understand the effect of reservoir turbidity distribution as a function of the selective withdrawal depth. This study applied the CE-QUAL-W2, a water quality and 2-dimensional hydrodynamic model, for simulating the hydrodynamic processes of the two reservoirs. Results indicate that, in the Andong reservoir, the turbidity of the released water with the water transfer tunnel was similar to that without the tunnel. However, in the Imha reservoir, the turbidity of the released water with the water transfer tunnel was lower than that without the tunnel. This can be attributed to the higher capacity of the Andong reservoir, which has double the storage of the Imha reservoir. Withdrawal turbidity in the Imha reservoir was investigated using the water transfer tunnel. This study applied three withdrawal selections as elevation (EL. 141.0 m, 146.5 m, and 152.0 m. The highest withdrawal turbidity resulted in EL. 141.0 m, which indicates that the high turbidity current is located at a vertical depth of about 20–30 m because of the density difference. These results will be helpful for understanding the release and selective withdrawal turbidity behaviors for a water transfer tunnel between two reservoirs.

Optimal reservoir operation policies using novel nested algorithms

Science.gov (United States)

Delipetrev, Blagoj; Jonoski, Andreja; Solomatine, Dimitri

2015-04-01

Historically, the two most widely practiced methods for optimal reservoir operation have been dynamic programming (DP) and stochastic dynamic programming (SDP). These two methods suffer from the so called "dual curse" which prevents them to be used in reasonably complex water systems. The first one is the "curse of dimensionality" that denotes an exponential growth of the computational complexity with the state - decision space dimension. The second one is the "curse of modelling" that requires an explicit model of each component of the water system to anticipate the effect of each system's transition. We address the problem of optimal reservoir operation concerning multiple objectives that are related to 1) reservoir releases to satisfy several downstream users competing for water with dynamically varying demands, 2) deviations from the target minimum and maximum reservoir water levels and 3) hydropower production that is a combination of the reservoir water level and the reservoir releases. Addressing such a problem with classical methods (DP and SDP) requires a reasonably high level of discretization of the reservoir storage volume, which in combination with the required releases discretization for meeting the demands of downstream users leads to computationally expensive formulations and causes the curse of dimensionality. We present a novel approach, named "nested" that is implemented in DP, SDP and reinforcement learning (RL) and correspondingly three new algorithms are developed named nested DP (nDP), nested SDP (nSDP) and nested RL (nRL). The nested algorithms are composed from two algorithms: 1) DP, SDP or RL and 2) nested optimization algorithm. Depending on the way we formulate the objective function related to deficits in the allocation problem in the nested optimization, two methods are implemented: 1) Simplex for linear allocation problems, and 2) quadratic Knapsack method in the case of nonlinear problems. The novel idea is to include the nested

Forecasting the consequences of accidental releases of radionuclides in the atmosphere from ensemble dispersion modelling

International Nuclear Information System (INIS)

Galmarini, S.; Bianconi, R.; Bellasio, R.; Graziani, G.

2001-01-01

The RTMOD system is presented as a tool for the intercomparison of long-range dispersion models as well as a system for support of decision making. RTMOD is an internet-based procedure that collects the results of more than 20 models used around the world to predict the transport and deposition of radioactive releases in the atmosphere. It allows the real-time acquisition of model results and their intercomparison. Taking advantage of the availability of several model results, the system can also be used as a tool to support decision making in case of emergency. The new concept of ensemble dispersion modelling is introduced which is the basis for the decision-making application of RTMOD. New statistical parameters are presented that allow gathering the results of several models to produce a single dispersion forecast. The devised parameters are presented and tested on the results of RTMOD exercises

The development and evaluation of a hydrological seasonal forecast system prototype for predicting spring flood volumes in Swedish rivers

Science.gov (United States)

Foster, Kean; Bertacchi Uvo, Cintia; Olsson, Jonas

2018-05-01

Hydropower makes up nearly half of Sweden's electrical energy production. However, the distribution of the water resources is not aligned with demand, as most of the inflows to the reservoirs occur during the spring flood period. This means that carefully planned reservoir management is required to help redistribute water resources to ensure optimal production and accurate forecasts of the spring flood volume (SFV) is essential for this. The current operational SFV forecasts use a historical ensemble approach where the HBV model is forced with historical observations of precipitation and temperature. In this work we develop and test a multi-model prototype, building on previous work, and evaluate its ability to forecast the SFV in 84 sub-basins in northern Sweden. The hypothesis explored in this work is that a multi-model seasonal forecast system incorporating different modelling approaches is generally more skilful at forecasting the SFV in snow dominated regions than a forecast system that utilises only one approach. The testing is done using cross-validated hindcasts for the period 1981-2015 and the results are evaluated against both climatology and the current system to determine skill. Both the multi-model methods considered showed skill over the reference forecasts. The version that combined the historical modelling chain, dynamical modelling chain, and statistical modelling chain performed better than the other and was chosen for the prototype. The prototype was able to outperform the current operational system 57 % of the time on average and reduce the error in the SFV by ˜ 6 % across all sub-basins and forecast dates.

Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input

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Jonas W. Pedersen

2016-09-01

Full Text Available High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper presents a way of updating conceptual rainfall-runoff models using Maximum a Posteriori estimation to determine the most likely parameter constellation at the current point in time. This is done by combining information from prior parameter distributions and the model goodness of fit over a predefined period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior standard deviations and lengths of the auto-calibration period on the resulting flow forecast performance are evaluated. We were able to demonstrate that, if properly tuned, the method leads to a significant increase in forecasting performance compared to a model without continuous auto-calibration. Delayed responses and erratic behaviour in the parameter variations are, however, observed and the choice of prior distributions and length of auto-calibration period is not straightforward.

Environmental transport and long-term exposure for tritium released in the biosphere

International Nuclear Information System (INIS)

Bergman, R.; Bergstroem, U.; Evans, S.

1979-01-01

Global cycling of tritium is studied with regard to long-term exposure and dose. Dose and dose commitment are calculated for releases at different latitudes to the troposphere, land and upper ocean layer, with particular regard to effects from release into recipients of intermediate size as, for example, the Baltic Sea. The global transport of tritium appears to be governed by first order kinetics. Compartment models based on linear differential equation systems, as used in this study, should therefore be adequate. The realism and applicability of ecological compartment models are analysed with respect to completeness of the systems of reservoirs and pathways as well as accuracy in assumed reservoir sizes and exchange rates. By introducing different biospheric reservoirs and transfer mechanisms, important carriers and recipients are identified for the analysis of tritium released to air, land and water. Terrestrial biota and groundwater are shown to be significant both with regard to reservoir sizes and influence on the land-troposphere and land-sea exchange of tritium. Model studies regarding the conversion of HT to HTO in different biospheric reservoirs indicate that an atmospheric release of HT may yield up to 1.7 times the dose commitment obtained after release of the same amount of tritium as HTO. The global collective dose commitment from a tropospheric release of tritium is 0.002-0.004 man.rem per Ci depending on the latitude at the release point. Release to the surface ocean layers gives a ten times lower collective dose. (author)

A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

Science.gov (United States)

Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

2017-04-01

Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of

a Stochastic Approach to Multiobjective Optimization of Large-Scale Water Reservoir Networks

Science.gov (United States)

Bottacin-Busolin, A.; Worman, A. L.

2013-12-01

A main challenge for the planning and management of water resources is the development of multiobjective strategies for operation of large-scale water reservoir networks. The optimal sequence of water releases from multiple reservoirs depends on the stochastic variability of correlated hydrologic inflows and on various processes that affect water demand and energy prices. Although several methods have been suggested, large-scale optimization problems arising in water resources management are still plagued by the high dimensional state space and by the stochastic nature of the hydrologic inflows. In this work, the optimization of reservoir operation is approached using approximate dynamic programming (ADP) with policy iteration and function approximators. The method is based on an off-line learning process in which operating policies are evaluated for a number of stochastic inflow scenarios, and the resulting value functions are used to design new, improved policies until convergence is attained. A case study is presented of a multi-reservoir system in the Dalälven River, Sweden, which includes 13 interconnected reservoirs and 36 power stations. Depending on the late spring and summer peak discharges, the lowlands adjacent to Dalälven can often be flooded during the summer period, and the presence of stagnating floodwater during the hottest months of the year is the cause of a large proliferation of mosquitos, which is a major problem for the people living in the surroundings. Chemical pesticides are currently being used as a preventive countermeasure, which do not provide an effective solution to the problem and have adverse environmental impacts. In this study, ADP was used to analyze the feasibility of alternative operating policies for reducing the flood risk at a reasonable economic cost for the hydropower companies. To this end, mid-term operating policies were derived by combining flood risk reduction with hydropower production objectives. The performance

Multimodel hydrological ensemble forecasts for the Baskatong catchment in Canada using the TIGGE database.

Science.gov (United States)

Tito Arandia Martinez, Fabian

2014-05-01

Adequate uncertainty assessment is an important issue in hydrological modelling. An important issue for hydropower producers is to obtain ensemble forecasts which truly grasp the uncertainty linked to upcoming streamflows. If properly assessed, this uncertainty can lead to optimal reservoir management and energy production (ex. [1]). The meteorological inputs to the hydrological model accounts for an important part of the total uncertainty in streamflow forecasting. Since the creation of the THORPEX initiative and the TIGGE database, access to meteorological ensemble forecasts from nine agencies throughout the world have been made available. This allows for hydrological ensemble forecasts based on multiple meteorological ensemble forecasts. Consequently, both the uncertainty linked to the architecture of the meteorological model and the uncertainty linked to the initial condition of the atmosphere can be accounted for. The main objective of this work is to show that a weighted combination of meteorological ensemble forecasts based on different atmospheric models can lead to improved hydrological ensemble forecasts, for horizons from one to ten days. This experiment is performed for the Baskatong watershed, a head subcatchment of the Gatineau watershed in the province of Quebec, in Canada. Baskatong watershed is of great importance for hydro-power production, as it comprises the main reservoir for the Gatineau watershed, on which there are six hydropower plants managed by Hydro-Québec. Since the 70's, they have been using pseudo ensemble forecast based on deterministic meteorological forecasts to which variability derived from past forecasting errors is added. We use a combination of meteorological ensemble forecasts from different models (precipitation and temperature) as the main inputs for hydrological model HSAMI ([2]). The meteorological ensembles from eight of the nine agencies available through TIGGE are weighted according to their individual performance and

Spatial Forecast of Landslides in Three Gorges Based On Spatial Data Mining

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Xianmin Wang

2009-03-01

Full Text Available The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc. China-Brazil Earth Resources Satellite (Cbers images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods.

Patterns of sediment accumulation in Watts Bar Reservoir based on 137Cesium

International Nuclear Information System (INIS)

Brandt, C.C.; Rose, K.A.; Cook, R.B.; Dearstone, K.C.; Brenkert, A.L.; Olsen, C.R.

1991-01-01

The US Department of Energy has recently undertaken an environmental restoration program designed to achieve remediation of hazardous materials released from the Oak Ridge Reservation (ORR). The distribution of 137 Cs was investigated in sediments from Watts Barr Reservoir and the Clinch River as a possible marker for other contaminants released from the ORR. We have performed additional analyses on the data gathered for this study to investigate possible relationships between 137 Cs accumulation and reservoir characteristics. We found that 137 Cs deposition correlates with sedimentation rate, and soft mud layers of cores have higher 137 Cs levels than sandy mud or eroded soils. No correlation was found with water depth, distance from shore or distance from release source, but it is important to note the data were not collected to test for these effects. We estimate Watts Barr Reservoir contains 267 Ci of 137 Cs, with 7% of this total in the top 16 cm of sediment, and potentially available for biological accumulation. 2 refs

Spillways Scheduling for Flood Control of Three Gorges Reservoir Using Mixed Integer Linear Programming Model

Directory of Open Access Journals (Sweden)

Maoyuan Feng

2014-01-01

Full Text Available This study proposes a mixed integer linear programming (MILP model to optimize the spillways scheduling for reservoir flood control. Unlike the conventional reservoir operation model, the proposed MILP model specifies the spillways status (including the number of spillways to be open and the degree of the spillway opened instead of reservoir release, since the release is actually controlled by using the spillway. The piecewise linear approximation is used to formulate the relationship between the reservoir storage and water release for a spillway, which should be open/closed with a status depicted by a binary variable. The control order and symmetry rules of spillways are described and incorporated into the constraints for meeting the practical demand. Thus, a MILP model is set up to minimize the maximum reservoir storage. The General Algebraic Modeling System (GAMS and IBM ILOG CPLEX Optimization Studio (CPLEX software are used to find the optimal solution for the proposed MILP model. The China’s Three Gorges Reservoir, whose spillways are of five types with the total number of 80, is selected as the case study. It is shown that the proposed model decreases the flood risk compared with the conventional operation and makes the operation more practical by specifying the spillways status directly.

Flood risk management for large reservoirs

International Nuclear Information System (INIS)

Poupart, M.

2006-01-01

Floods are a major risk for dams: uncontrolled reservoir water level may cause dam overtopping, and then its failure, particularly for fill dams. Poor control of spillway discharges must be taken into consideration too, as it can increase the flood consequences downstream. In both cases, consequences on the public or on properties may be significant. Spillway design to withstand extreme floods is one response to these risks, but must be complemented by strict operating rules: hydrological forecasting, surveillance and periodic equipment controls, operating guides and the training of operators are mandatory too, in order to guarantee safe operations. (author)

On the flood forecasting at the Bulgarian part of Struma River Basin

International Nuclear Information System (INIS)

Dimitrov, Dobri

2004-01-01

Struma is a mountain river flowing from North to South, from Bulgaria through Greece up to the Aegean Sea. It generates flush floods of snow melt - rainfall type mainly in the late spring. Flood forecasting there is needed to improve the flood mitigation measures at the Bulgarian territory of the basin as well as for effective reservoir management downstream Bulgarian border, secure flood handling at Greek territory and generally decrease the flood hazard. The paper summarizes the range of activities in the basin including: - the installation of automatic telemetric hydro meteorological observation network; - review of the results of relevant past projects; - analysis of historical hydro meteorological data; - design and calibration of flood forecasting models; - demonstrating the possibility to issue flood warnings with certain lead time and accuracy; - recent efforts to increase the lead time of the hydrological forecasts, applying forecasts from High Resolution Limited Area meteorological models and other activities in the frame of the EC 5th FP EFFS project.(Author)

Evaluation of statistical models for forecast errors from the HBV model

Science.gov (United States)

Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

2010-04-01

SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.

Techniques for Reaeration of Hydropower Releases.

Science.gov (United States)

1983-02-01

release improvement. However, selected reservoir aeration studies not conducted primarily for improving hydroturbine releases but which have application...for hydroturbine release reaeration were also reviewed. Because oxygen transfer mechanisms are vitally important to the development of more efficient...the key words turbine aeration, turbine vent, turbine I’ aspiration, hydroturbine aeration, tailrace aeration, draft tube vent, and vacuum breaker. A

Impact of real-time measurements for data assimilation in reservoir simulation

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R; Krosche, M [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Pajonk, O [TU Braunschweig (Germany). Inst. fuer Wissenschaftliches Rechnen; Myrland, T [Morges Teknisk-Naturvitenskapelige Univ. (NTNU), Trondheim (Germany)

2008-10-23

This paper gives an overview on the conceptual background of data assimilation techniques. The framework of sequential data assimilation as described for the ensemble Kalman filter implementation allows a continuous integration of new measurement data. The initial diversity of ensemble members will be critical for the assimilation process and the ability to successfully assimilate measurement data. At the same time the initial ensemble will impact the propagation of uncertainties with crucial consequences for production forecasts. Data assimilation techniques have complimentary features compared to other optimization techniques built on selection or regression schemes. Specifically, EnKF is applicable to real field cases and defines an important perspective for facilitating continuous reservoir simulation model updates in a reservoir life cycle. (orig.)

Reservoir characterization and performance predictions for the E.N. Woods lease

Energy Technology Data Exchange (ETDEWEB)

Aka-Milan, Francis A.

2000-07-07

The task of this work was to evaluate the past performance of the E.N. WOODS Unit and to forecast its future economic performance by taking into consideration the geology, petrophysics and production history of the reservoir. The Decline Curve Analysis feature of the Appraisal of Petroleum Properties including Taxation Systems (EDAPT) software along with the Production Management Systems (PMS) software were used to evaluate the original volume of hydrocarbon in place and estimate the reserve. The Black Oil Simulator (BOAST II) was then used to model the waterflooding operation and estimate the incremental oil production attributable to the water injection. BOAST II was also used to predict future performance of the reservoir.

2013 Gulf of Mexico Hypoxia Forecast

Science.gov (United States)

Scavia, Donald; Evans, Mary Anne; Obenour, Dan

2013-01-01

The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 7,316 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 18,900 square kilometers (95% credible interval, 13,400 to 24,200), the 7th largest reported and about the size of New Jersey. Our forecast hypoxic volume is 74.5 km3 (95% credible interval, 51.5 to 97.0), also the 7th largest on record.

Cognitive methodology for forecasting oil and gas industry using pattern-based neural information technologies

Science.gov (United States)

Gafurov, O.; Gafurov, D.; Syryamkin, V.

2018-05-01

The paper analyses a field of computer science formed at the intersection of such areas of natural science as artificial intelligence, mathematical statistics, and database theory, which is referred to as "Data Mining" (discovery of knowledge in data). The theory of neural networks is applied along with classical methods of mathematical analysis and numerical simulation. The paper describes the technique protected by the patent of the Russian Federation for the invention “A Method for Determining Location of Production Wells during the Development of Hydrocarbon Fields” [1–3] and implemented using the geoinformation system NeuroInformGeo. There are no analogues in domestic and international practice. The paper gives an example of comparing the forecast of the oil reservoir quality made by the geophysicist interpreter using standard methods and the forecast of the oil reservoir quality made using this technology. The technical result achieved shows the increase of efficiency, effectiveness, and ecological compatibility of development of mineral deposits and discovery of a new oil deposit.

Evaluation Of Statistical Models For Forecast Errors From The HBV-Model

Science.gov (United States)

Engeland, K.; Kolberg, S.; Renard, B.; Stensland, I.

2009-04-01

Three statistical models for the forecast errors for inflow to the Langvatn reservoir in Northern Norway have been constructed and tested according to how well the distribution and median values of the forecasts errors fit to the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order autoregressive model was constructed for the forecast errors. The parameters were conditioned on climatic conditions. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order autoregressive model was constructed for the forecast errors. For the last model positive and negative errors were modeled separately. The errors were first NQT-transformed before a model where the mean values were conditioned on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: We wanted a) the median values to be close to the observed values; b) the forecast intervals to be narrow; c) the distribution to be correct. The results showed that it is difficult to obtain a correct model for the forecast errors, and that the main challenge is to account for the auto-correlation in the errors. Model 1 and 2 gave similar results, and the main drawback is that the distributions are not correct. The 95% forecast intervals were well identified, but smaller forecast intervals were over-estimated, and larger intervals were under-estimated. Model 3 gave a distribution that fits better, but the median values do not fit well since the auto-correlation is not properly accounted for. If the 95% forecast interval is of interest, Model 2 is recommended. If the whole distribution is of interest, Model 3 is recommended.

Climate Change Assessment of Precipitation in Tandula Reservoir System

Science.gov (United States)

Jaiswal, Rahul Kumar; Tiwari, H. L.; Lohani, A. K.

2018-02-01

The precipitation is the principle input of hydrological cycle affect availability of water in spatial and temporal scale of basin due to widely accepted climate change. The present study deals with the statistical downscaling using Statistical Down Scaling Model for rainfall of five rain gauge stations (Ambagarh, Bhanpura, Balod, Chamra and Gondli) in Tandula, Kharkhara and Gondli reservoirs of Chhattisgarh state of India to forecast future rainfall in three different periods under SRES A1B and A2 climatic forcing conditions. In the analysis, twenty-six climatic variables obtained from National Centers for Environmental Prediction were used and statistically tested for selection of best-fit predictors. The conditional process based statistical correlation was used to evolve multiple linear relations in calibration for period of 1981-1995 was tested with independent data of 1996-2003 for validation. The developed relations were further used to predict future rainfall scenarios for three different periods 2020-2035 (FP-1), 2046-2064 (FP-2) and 2081-2100 (FP-3) and compared with monthly rainfalls during base period (1981-2003) for individual station and all three reservoir catchments. From the analysis, it has been found that most of the rain gauge stations and all three reservoir catchments may receive significant less rainfall in future. The Thiessen polygon based annual and seasonal rainfall for different catchments confirmed a reduction of seasonal rainfall from 5.1 to 14.1% in Tandula reservoir, 11-19.2% in Kharkhara reservoir and 15.1-23.8% in Gondli reservoir. The Gondli reservoir may be affected the most in term of water availability in future prediction periods.

Targeted electrohydrodynamic printing for micro-reservoir drug delivery systems

International Nuclear Information System (INIS)

Hwang, Tae Heon; Kim, Jin Bum; Yang, Da Som; Ryu, WonHyoung; Park, Yong-il

2013-01-01

Microfluidic drug delivery systems consisting of a drug reservoir and microfluidic channels have shown the possibility of simple and robust modulation of drug release rate. However, the difficulty of loading a small quantity of drug into drug reservoirs at a micro-scale limited further development of such systems. Electrohydrodynamic (EHD) printing was employed to fill micro-reservoirs with controlled amount of drugs in the range of a few hundreds of picograms to tens of micrograms with spatial resolution of as small as 20 µm. Unlike most EHD systems, this system was configured in combination with an inverted microscope that allows in situ targeting of drug loading at micrometer scale accuracy. Methylene blue and rhodamine B were used as model drugs in distilled water, isopropanol and a polymer solution of a biodegradable polymer and dimethyl sulfoxide (DMSO). Also tetracycline-HCl/DI water was used as actual drug ink. The optimal parameters of EHD printing to load an extremely small quantity of drug into microscale drug reservoirs were investigated by changing pumping rates, the strength of an electric field and drug concentration. This targeted EHD technique was used to load drugs into the microreservoirs of PDMS microfluidic drug delivery devices and their drug release performance was demonstrated in vitro. (paper)

The Potential of a Surfactant/Polymer Flood in a Middle Eastern Reservoir

Directory of Open Access Journals (Sweden)

Meshal Algharaib

2012-01-01

Full Text Available An integrated full-field reservoir simulation study has been performed to determine the reservoir management and production strategies in a mature sandstone reservoir. The reservoir is a candidate for an enhanced oil recovery process or otherwise subject to abandonment. Based on its charateristics, the reservoir was found to be most suited for a surfactant/polymer (SP flood. The study started with a large data gathering and the building of a full-field three-dimensional geological model. Subsequently, a full field simulation model was built and used to history match the water flood. The history match of the water flood emphasizes the areas with remaining high oil saturations, establishes the initial condition of the reservoir for an SP flood, and generates a forecast of reserves for continued water flood operations. A sector model was constructed from the full field model and then used to study different design parameters to maximize the project profitability from the SP flood. An economic model, based on the estimated recovery, residual oil in-place, oil price, and operating costs, has been implemented in order to optimize the project profitability. The study resulted in the selection of surfactant and polymer concentrations and slug size that yielded the best economic returns when applied in this reservoir. The study shows that, in today’s oil prices, surfactant/polymer flood when applied in this reservoir has increased the ultimate oil recovery and provide a significant financial returns.

Using analogs to generate production forecasts in Faja

Energy Technology Data Exchange (ETDEWEB)

Garcia Lugo, Rolando A. [Repsol (Canada)

2011-07-01

In the Carabobol Block, extra heavy oil will be produced by cold production from Miocene Morical Member sands. Many parameters such as pressure, temperature, solution gas oil ratio and viscosity variation significantly impact well productivity; unfortunately little information is available on the Carabobol Block. The aim of this paper is to provide a new methodology for using analog data to develop fluid properties correlations and a future production profile. Data from the analog neighbour field in the Orinoco oil belt was used. A methodology using scatter data was successfully applied for the Carabobol Block and fluid composition, a complete PVT and an analytical forecast were found and confirmed with actual laboratory data and a gross numerical model. This study showed that analog data can be used as a first approach to assess initial reservoir conditions and fluid properties and to generate production forecasts.

Research on classified real-time flood forecasting framework based on K-means cluster and rough set.

Science.gov (United States)

Xu, Wei; Peng, Yong

2015-01-01

This research presents a new classified real-time flood forecasting framework. In this framework, historical floods are classified by a K-means cluster according to the spatial and temporal distribution of precipitation, the time variance of precipitation intensity and other hydrological factors. Based on the classified results, a rough set is used to extract the identification rules for real-time flood forecasting. Then, the parameters of different categories within the conceptual hydrological model are calibrated using a genetic algorithm. In real-time forecasting, the corresponding category of parameters is selected for flood forecasting according to the obtained flood information. This research tests the new classified framework on Guanyinge Reservoir and compares the framework with the traditional flood forecasting method. It finds that the performance of the new classified framework is significantly better in terms of accuracy. Furthermore, the framework can be considered in a catchment with fewer historical floods.

Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

Science.gov (United States)

Yu, Pao-Shan; Yang, Tao-Chang; Chen, Szu-Yin; Kuo, Chen-Min; Tseng, Hung-Wei

2017-09-01

This study aims to compare two machine learning techniques, random forests (RF) and support vector machine (SVM), for real-time radar-derived rainfall forecasting. The real-time radar-derived rainfall forecasting models use the present grid-based radar-derived rainfall as the output variable and use antecedent grid-based radar-derived rainfall, grid position (longitude and latitude) and elevation as the input variables to forecast 1- to 3-h ahead rainfalls for all grids in a catchment. Grid-based radar-derived rainfalls of six typhoon events during 2012-2015 in three reservoir catchments of Taiwan are collected for model training and verifying. Two kinds of forecasting models are constructed and compared, which are single-mode forecasting model (SMFM) and multiple-mode forecasting model (MMFM) based on RF and SVM. The SMFM uses the same model for 1- to 3-h ahead rainfall forecasting; the MMFM uses three different models for 1- to 3-h ahead forecasting. According to forecasting performances, it reveals that the SMFMs give better performances than MMFMs and both SVM-based and RF-based SMFMs show satisfactory performances for 1-h ahead forecasting. However, for 2- and 3-h ahead forecasting, it is found that the RF-based SMFM underestimates the observed radar-derived rainfalls in most cases and the SVM-based SMFM can give better performances than RF-based SMFM.

Decision Support System for Reservoir Management and Operation in Africa

Science.gov (United States)

Navar, D. A.

2016-12-01

Africa is currently experiencing a surge in dam construction for flood control, water supply and hydropower production, but ineffective reservoir management has caused problems in the region, such as water shortages, flooding and loss of potential hydropower generation. Our research aims to remedy ineffective reservoir management by developing a novel Decision Support System(DSS) to equip water managers with a technical planning tool based on the state of the art in hydrological sciences. The DSS incorporates a climate forecast model, a hydraulic model of the watershed, and an optimization model to effectively plan for the operation of a system of cascade large-scale reservoirs for hydropower production, while treating water supply and flood control as constraints. Our team will use the newly constructed hydropower plants in the Omo Gibe basin of Ethiopia as the test case. Using the basic HIDROTERM software developed in Brazil, the General Algebraic Modeling System (GAMS) utilizes a combination of linear programing (LP) and non-linear programming (NLP) in conjunction with real time hydrologic and energy demand data to optimize the monthly and daily operations of the reservoir system. We compare the DSS model results with the current reservoir operating policy used by the water managers of that region. We also hope the DSS will eliminate the current dangers associated with the mismanagement of large scale water resources projects in Africa.

Short-term forecasts of energy use and energy supply 2012-2014. Spring 2013; Kortsiktsprognos - Oever energianvaendning och energitillfoersel 2012-2014, Vaaren 2013

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-03-15

This report provides a description of the Swedish energy system in 2011 and an assessment of its development between 2012 - 2014. The forecast shall be interpreted as a consequence of the limitations and assumptions underlying it. Thus, it is important to remember that if any of the conditions or assumptions change, the forecast's results will also change. The forecast is based on economic conditions that have been developed from the National Institute of Economic Trend. Other conditions such as electricity prices, fuel prices, outdoor temperature and inflow into reservoirs are based on information available up to January 2013, when forecasting began.

Hydraulic plant generation forecasting in Colombian power market using ANFIS

Energy Technology Data Exchange (ETDEWEB)

Moreno, Julian [Computer Science Department, Carrera 80 No. 65-223 Bloque M8A, Universidad Nacional de Colombia, Medellin (Colombia)

2009-05-15

In this paper an ANFIS model (adaptive neuro-fuzzy inference system) is proposed to forecast the monthly ideal generation of an agent with a hydraulic plant within the Colombian power market. The proposed model considers several factors as the plant's reservoir level, the expected hydraulic contributions of the rivers which feed it, and the expected weather conditions represented by the SST anomaly forecast in Nino 3.4 zone. The fitness of such model is measured with real data of a particular agent from period 2002-2007 and it is compared against a multiple linear regression model. The obtained results show a considerable decrease of the mean percentage error, which is an evidence of its validity and possible application to other agents. (author)

Hydraulic plant generation forecasting in Colombian power market using ANFIS

International Nuclear Information System (INIS)

Moreno, Julian

2009-01-01

In this paper an ANFIS model (adaptive neuro-fuzzy inference system) is proposed to forecast the monthly ideal generation of an agent with a hydraulic plant within the Colombian power market. The proposed model considers several factors as the plant's reservoir level, the expected hydraulic contributions of the rivers which feed it, and the expected weather conditions represented by the SST anomaly forecast in Nino 3.4 zone. The fitness of such model is measured with real data of a particular agent from period 2002-2007 and it is compared against a multiple linear regression model. The obtained results show a considerable decrease of the mean percentage error, which is an evidence of its validity and possible application to other agents. (author)

Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

Science.gov (United States)

Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

2018-05-01

Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

Application of artificial intelligence to forecast hydrocarbon production from shales

Directory of Open Access Journals (Sweden)

Palash Panja

2018-03-01

Full Text Available Artificial intelligence (AI methods and applications have recently gained a great deal of attention in many areas, including fields of mathematics, neuroscience, economics, engineering, linguistics, gaming, and many others. This is due to the surge of innovative and sophisticated AI techniques applications to highly complex problems as well as the powerful new developments in high speed computing. Various applications of AI in everyday life include machine learning, pattern recognition, robotics, data processing and analysis, etc. The oil and gas industry is not behind either, in fact, AI techniques have recently been applied to estimate PVT properties, optimize production, predict recoverable hydrocarbons, optimize well placement using pattern recognition, optimize hydraulic fracture design, and to aid in reservoir characterization efforts. In this study, three different AI models are trained and used to forecast hydrocarbon production from hydraulically fractured wells. Two vastly used artificial intelligence methods, namely the Least Square Support Vector Machine (LSSVM and the Artificial Neural Networks (ANN, are compared to a traditional curve fitting method known as Response Surface Model (RSM using second order polynomial equations to determine production from shales. The objective of this work is to further explore the potential of AI in the oil and gas industry. Eight parameters are considered as input factors to build the model: reservoir permeability, initial dissolved gas-oil ratio, rock compressibility, gas relative permeability, slope of gas oil ratio, initial reservoir pressure, flowing bottom hole pressure, and hydraulic fracture spacing. The range of values used for these parameters resemble real field scenarios from prolific shale plays such as the Eagle Ford, Bakken, and the Niobrara in the United States. Production data consists of oil recovery factor and produced gas-oil ratio (GOR generated from a generic hydraulically

Forecasting metal prices: Do forecasters herd?

DEFF Research Database (Denmark)

Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

2013-01-01

We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

Optimization In Searching Daily Rule Curve At Mosul Regulating Reservoir, North Iraq Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Thair M. Al-Taiee

2013-05-01

Full Text Available To obtain optimal operating rules for storage reservoirs, large numbers of simulation and optimization models have been developed over the past several decades, which vary significantly in their mechanisms and applications. Rule curves are guidelines for long term reservoir operation. An efficient technique is required to find the optimal rule curves that can mitigate water shortage in long term operation. The investigation of developed Genetic Algorithm (GA technique, which is an optimization approach base on the mechanics of natural selection, derived from the theory of natural evolution, was carried out to through the application to predict the daily rule curve of  Mosul regulating reservoir in Iraq.  Record daily inflows, outflow, water level in the reservoir for 19 year (1986-1990 and (1994-2007 were used in the developed model for assessing the optimal reservoir operation. The objective function is set to minimize the annual sum of squared deviation from the desired downstream release and desired storage volume in the reservoir. The decision variables are releases, storage volume, water level and outlet (demand from the reservoir. The results of the GA model gave a good agreement during the comparison with the actual rule curve and the designed rating curve of the reservoir. The simulated result shows that GA-derived policies are promising and competitive and can be effectively used for daily reservoir operation in addition to the rational monthly operation and predicting also rating curve of reservoirs.

Simulation-optimization model of reservoir operation based on target storage curves

Directory of Open Access Journals (Sweden)

Hong-bin Fang

2014-10-01

Full Text Available This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transfer-supply projects. The joint operating rules include a water diversion rule to determine the amount of diverted water in a period, a hedging rule based on an aggregated reservoir to determine the total release from the system, and a storage allocation rule to specify the release from each reservoir. A simulation-optimization model was established to optimize the key points of the water diversion curves, the hedging rule curves, and the target storage curves using the improved particle swarm optimization (IPSO algorithm. The multi-reservoir water supply system located in Liaoning Province, China, including a water transfer-supply project, was employed as a case study to verify the effectiveness of the proposed join operating rules and target storage curves. The results indicate that the proposed operating rules are suitable for the complex system. The storage allocation rule based on target storage curves shows an improved performance with regard to system storage distribution.

Multiobjective Optimization Modeling Approach for Multipurpose Single Reservoir Operation

Directory of Open Access Journals (Sweden)

Iosvany Recio Villa

2018-04-01

Full Text Available The water resources planning and management discipline recognizes the importance of a reservoir’s carryover storage. However, mathematical models for reservoir operation that include carryover storage are scarce. This paper presents a novel multiobjective optimization modeling framework that uses the constraint-ε method and genetic algorithms as optimization techniques for the operation of multipurpose simple reservoirs, including carryover storage. The carryover storage was conceived by modifying Kritsky and Menkel’s method for reservoir design at the operational stage. The main objective function minimizes the cost of the total annual water shortage for irrigation areas connected to a reservoir, while the secondary one maximizes its energy production. The model includes operational constraints for the reservoir, Kritsky and Menkel’s method, irrigation areas, and the hydropower plant. The study is applied to Carlos Manuel de Céspedes reservoir, establishing a 12-month planning horizon and an annual reliability of 75%. The results highly demonstrate the applicability of the model, obtaining monthly releases from the reservoir that include the carryover storage, degree of reservoir inflow regulation, water shortages in irrigation areas, and the energy generated by the hydroelectric plant. The main product is an operational graph that includes zones as well as rule and guide curves, which are used as triggers for long-term reservoir operation.

Extracting maximum petrophysical and geological information from a limited reservoir database

Energy Technology Data Exchange (ETDEWEB)

Ali, M.; Chawathe, A.; Ouenes, A. [New Mexico Institute of Mining and Technology, Socorro, NM (United States)] [and others

1997-08-01

The characterization of old fields lacking sufficient core and log data is a challenging task. This paper describes a methodology that uses new and conventional tools to build a reliable reservoir model for the Sulimar Queen field. At the fine scale, permeability measured on a fine grid with a minipermeameter was used in conjunction with the petrographic data collected on multiple thin sections. The use of regression analysis and a newly developed fuzzy logic algorithm led to the identification of key petrographic elements which control permeability. At the log scale, old gamma ray logs were first rescaled/calibrated throughout the entire field for consistency and reliability using only four modem logs. Using data from one cored well and the rescaled gamma ray logs, correlations between core porosity, permeability, total water content and gamma ray were developed to complete the small scale characterization. At the reservoir scale, outcrop data and the rescaled gamma logs were used to define the reservoir structure over an area of ten square miles where only 36 wells were available. Given the structure, the rescaled gamma ray logs were used to build the reservoir volume by identifying the flow units and their continuity. Finally, history-matching results constrained to the primary production were used to estimate the dynamic reservoir properties such as relative permeabilities to complete the characterization. The obtained reservoir model was tested by forecasting the waterflood performance and which was in good agreement with the actual performance.

Assessing Performance of Multipurpose Reservoir System Using Two-Point Linear Hedging Rule

Science.gov (United States)

Sasireka, K.; Neelakantan, T. R.

2017-07-01

Reservoir operation is the one of the important filed of water resource management. Innovative techniques in water resource management are focussed at optimizing the available water and in decreasing the environmental impact of water utilization on the natural environment. In the operation of multi reservoir system, efficient regulation of the release to satisfy the demand for various purpose like domestic, irrigation and hydropower can lead to increase the benefit from the reservoir as well as significantly reduces the damage due to floods. Hedging rule is one of the emerging techniques in reservoir operation, which reduce the severity of drought by accepting number of smaller shortages. The key objective of this paper is to maximize the minimum power production and improve the reliability of water supply for municipal and irrigation purpose by using hedging rule. In this paper, Type II two-point linear hedging rule is attempted to improve the operation of Bargi reservoir in the Narmada basin in India. The results obtained from simulation of hedging rule is compared with results from Standard Operating Policy, the result shows that the application of hedging rule significantly improved the reliability of water supply and reliability of irrigation release and firm power production.

Towards a better knowledge of flash flood forecasting at the Three Gorges Region: Progress over the past decade and challenges ahead

Science.gov (United States)

Li, Zhe; Yang, Dawen; Yang, Hanbo; Wu, Tianjiao; Xu, Jijun; Gao, Bing; Xu, Tao

2015-04-01

The study area, the Three Gorges Region (TGR), plays a critical role in predicting the floods drained into the Three Gorges Reservoir, as reported local floods often exceed 10000m3/s during rainstorm events and trigger fast as well as significant impacts on the Three Gorges Reservoir's regulation. Meanwhile, it is one of typical mountainous areas in China, which is located in the transition zone between two monsoon systems: the East Asian monsoon and the South Asian (Indian) monsoon. This climatic feature, combined with local irregular terrains, has shaped complicated rainfall-runoff regimes in this focal region. However, due to the lack of high-resolution hydrometeorological data and physically-based hydrologic modeling framework, there was little knowledge about rainfall variability and flood pattern in this historically ungauged region, which posed great uncertainties to flash flood forecasting in the past. The present study summarize latest progresses of regional flash floods monitoring and prediction, including installation of a ground-based Hydrometeorological Observation Network (TGR-HMON), application of a regional geomorphology-based hydrological model (TGR-GBHM), development of an integrated forecasting and modeling system (TGR-INFORMS), and evaluation of quantitative precipitation estimations (QPE) and quantitative precipitation forecasting (QPF) products in TGR flash flood forecasting. With these continuing efforts to improve the forecasting performance of flash floods in TGR, we have addressed several critical issues: (1) Current observation network is still insufficient to capture localized rainstorms, and weather radar provides valuable information to forecast flash floods induced by localized rainstorms, although current radar QPE products can be improved substantially in future; (2) Long-term evaluation shows that the geomorphology-based distributed hydrologic model (GBHM) is able to simulate flash flooding processes reasonably, while model

Extending to seasonal scales the current usage of short range weather forecasts and climate projections for water management in Spain

Science.gov (United States)

Rodriguez-Camino, Ernesto; Voces, José; Sánchez, Eroteida; Navascues, Beatriz; Pouget, Laurent; Roldan, Tamara; Gómez, Manuel; Cabello, Angels; Comas, Pau; Pastor, Fernando; Concepción García-Gómez, M.°; José Gil, Juan; Gil, Delfina; Galván, Rogelio; Solera, Abel

2016-04-01

This presentation, first, briefly describes the current use of weather forecasts and climate projections delivered by AEMET for water management in Spain. The potential use of seasonal climate predictions for water -in particular dams- management is then discussed more in-depth, using a pilot experience carried out by a multidisciplinary group coordinated by AEMET and DG for Water of Spain. This initiative is being developed in the framework of the national implementation of the GFCS and the European project, EUPORIAS. Among the main components of this experience there are meteorological and hydrological observations, and an empirical seasonal forecasting technique that provides an ensemble of water reservoir inflows. These forecasted inflows feed a prediction model for the dam state that has been adapted for this purpose. The full system is being tested retrospectively, over several decades, for selected water reservoirs located in different Spanish river basins. The assessment includes an objective verification of the probabilistic seasonal forecasts using standard metrics, and the evaluation of the potential social and economic benefits, with special attention to drought and flooding conditions. The methodology of implementation of these seasonal predictions in the decision making process is being developed in close collaboration with final users participating in this pilot experience.

Forecasting world natural gas supply

International Nuclear Information System (INIS)

Al-Fattah, S. M.; Startzman, R. A.

2000-01-01

Using the multi-cyclic Hubert approach, a 53 country-specific gas supply model was developed which enables production forecasts for virtually all of the world's gas. Supply models for some organizations such as OPEC, non-OPEC and OECD were also developed and analyzed. Results of the modeling study indicate that the world's supply of natural gas will peak in 2014, followed by an annual decline at the rate of one per cent per year. North American gas production is reported to be currently at its peak with 29 Tcf/yr; Western Europe will reach its peak supply in 2002 with 12 Tcf. According to this forecast the main sources of natural gas supply in the future will be the countries of the former Soviet Union and the Middle East. Between them, they possess about 62 per cent of the world's ultimate recoverable natural gas (4,880 Tcf). It should be noted that these estimates do not include unconventional gas resulting from tight gas reservoirs, coalbed methane, gas shales and gas hydrates. These unconventional sources will undoubtedly play an important role in the gas supply in countries such as the United States and Canada. 18 refs., 2 tabs., 18 figs

Assessment of Climate Change Effects on Shahcheraghi Reservoir Inflow

Directory of Open Access Journals (Sweden)

M. E. Banihabib

2016-10-01

Full Text Available Introduction: Forecasting the inflow to the reservoir is important issues due to the limited water resources and the importance of optimal utilization of reservoirs to meet the need for drinking, industry and agriculture in future time periods. In the meantime, ignoring the effects of climate change on meteorological and hydrological parameters and water resources in long-term planning of water resources cause inaccuracy. It is essential to assess the impact of climate change on reservoir operation in arid regions. In this research, climate change impact on hydrological and meteorological variables of the Shahcheragh dam basin, in Semnan Province, was studied using an integrated model of climate change assessment. Materials and Methods: The case study area of this study was located in Damghan Township, Semnan Province, Iran. It is an arid zone. The case study area is a part of the Iran Central Desert. The basin is in 12 km north of the Damghan City and between 53° E to 54° 30’ E longitude and 36° N to 36° 30’ N latitude. The area of the basin is 1,373 km2 with average annual inflow around 17.9 MCM. Total actual evaporation and average annual rainfall are 1,986 mm and 137 mm, respectively. This case study is chosen to test proposed framework for assessment of climate change impact hydrological and meteorological variables of the basin. In the proposed model, LARS-WG and ANN sub-models (7 sub models with a combination of different inputs such as temperature, precipitation and also solar radiation were used for downscaling daily outputs of CGCM3 model under 3 emission scenarios, A2, B1 and A1B and reservoir inflow simulation, respectively. LARS-WG was tested in 99% confidence level before using it as downscaling model and feed-forward neural network was used as raifall-runoff model. Moreover, the base period data (BPD, 1990-2008, were used for calibration. Finally, reservoir inflow was simulated for future period data (FPD of 2015-2044 and

[Research progress on phosphorus budgets and regulations in reservoirs].

Science.gov (United States)

Shen, Xiao; Li, Xu; Zhang, Wang-shou

2014-12-01

Phosphorus is an important limiting factor of water eutrophication. A clear understanding of its budget and regulated method is fundamental for reservoir ecological health. In order to pro- mote systematic research further and improve phosphorus regulation system, the budget balance of reservoir phosphorus and its influencing factors were concluded, as well as conventional regulation and control measures. In general, the main phosphorus sources of reservoirs include upstream input, overland runoff, industrial and domestic wastewater, aquaculture, atmospheric deposition and sediment release. Upstream input is the largest phosphorus source among them. The principal output path of phosphorus is the flood discharge, the emission load of which is mainly influenced by drainage patterns. In addition, biological harvest also can export a fraction of phosphorus. There are some factors affecting the reservoir phosphorus balance, including reservoirs' function, hydrological conditions, physical and chemical properties of water, etc. Therefore, the phosphorus budgets of different reservoirs vary greatly, according to different seasons and regions. In order to reduce the phosphorus loading in reservoirs, some methods are carried out, including constructed wetlands, prefix reservoir, sediment dredging, biomanipulation, etc. Different methods need to be chosen and combined according to different reservoirs' characteristics and water quality management goals. Thus, in the future research, it is reasonable to highlight reservoir ecological characteristics and proceed to a complete and systematic analysis of the inherent complexity of phosphorus budget and its impact factors for the reservoirs' management. Besides, the interaction between phosphorus budget and other nutrients in reservoirs also needs to be conducted. It is fundamental to reduce the reservoirs' phosphorus loading to establish a scientific and improved management system based on those researches.

Influence of break structures on the distribution of radionuclides in bottom sediments of the Kyiv reservoir

International Nuclear Information System (INIS)

Shestopalov, V.M.; Lyal'ko, V.I.; Fedorovskij, A.D.; Sirenko, L.A.; Khodorovskij, A.Ya.

2000-01-01

We study the distribution of radionuclides in bottom sediments of the Kyiv reservoir on the basis of research of adjacent territory break - block structures with deciphering space-born images and ground measurements and forecast the occurrence of extreme situations due to the redistribution of bottom water flows and sediments of radionuclides

Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

KAUST Repository

Katterbauer, Klemens

2015-11-18

Increasing complexity of hydrocarbon projects and the request for higher recovery rates have driven the oil-and-gas industry to look for a more-detailed understanding of the subsurface formation to optimize recovery of oil and profitability. Despite the significant successes of geophysical techniques in determining changes within the reservoir, the benefits from individually mapping the information are limited. Although seismic techniques have been the main approach for imaging the subsurface, the weak density contrast between water and oil has made electromagnetic (EM) technology an attractive complement to improve fluid distinction, especially for high-saline water. This crosswell technology assumes greater importance for obtaining higher-resolution images of the interwell regions to more accurately characterize the reservoir and track fluid-front developments. In this study, an ensemble-Kalman-based history-matching framework is proposed for directly incorporating crosswell time-lapse seismic and EM data into the history-matching process. The direct incorporation of the time-lapse seismic and EM data into the history-matching process exploits the complementarity of these data to enhance subsurface characterization, to incorporate interwell information, and to avoid biases that may be incurred from separate inversions of the geophysical data for attributes. An extensive analysis with 2D and realistic 3D reservoirs illustrates the robustness and enhanced forecastability of critical reservoir variables. The 2D reservoir provides a better understanding of the connection between fluid discrimination and enhanced history matches, and the 3D reservoir demonstrates its applicability to a realistic reservoir. History-matching enhancements (in terms of reduction in the history-matching error) when incorporating both seismic and EM data averaged approximately 50% for the 2D case, and approximately 30% for the 3D case, and permeability estimates were approximately 25

Thermal mapping studies at Kadra reservoir near Kaiga generating station site

International Nuclear Information System (INIS)

Ravi, P.M.; Nayak, P.D.; Sudhakar, J.; Mishra, D.G.; Hegde, A.G.

2007-01-01

An inherent problem in nuclear and thermal power plants are the release of heat energy into the environment through cooling system to water bodies such as lakes, rivers, estuaries and oceans. Two NPPs of Kaiga Generating Station, discharge the thermal effluent to the nearby Kadra reservoir. This paper presents the results of three year long comprehensive thermal mapping studies conducted by ESL, KGS as part of the Thermal Ecological Studies sponsored by Board of Research in Nuclear Sciences (BRNS), Department of Atomic Energy. Present studies clearly demonstrate that the thermally influenced zone in the reservoir is limited to a small volume of the reservoir and is not likely to lead any irreversible adverse impact on the ecosystem of the reservoir. (author)

Forecasting Flare Activity Using Deep Convolutional Neural Networks

Science.gov (United States)

Hernandez, T.

2017-12-01

Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

Estimating reservoir permeability from gravity current modeling of CO2 flow at Sleipner storage project, North Sea

Science.gov (United States)

Cowton, L. R.; Neufeld, J. A.; Bickle, M.; White, N.; White, J.; Chadwick, A.

2017-12-01

Vertically-integrated gravity current models enable computationally efficient simulations of CO2 flow in sub-surface reservoirs. These simulations can be used to investigate the properties of reservoirs by minimizing differences between observed and modeled CO2 distributions. At the Sleipner project, about 1 Mt yr-1 of supercritical CO2 is injected at a depth of 1 km into a pristine saline aquifer with a thick shale caprock. Analysis of time-lapse seismic reflection surveys shows that CO2 is distributed within 9 discrete layers. The trapping mechanism comprises a stacked series of 1 m thick, impermeable shale horizons that are spaced at 30 m intervals through the reservoir. Within the stratigraphically highest reservoir layer, Layer 9, a submarine channel deposit has been mapped on the pre-injection seismic survey. Detailed measurements of the three-dimensional CO2 distribution within Layer 9 have been made using seven time-lapse surveys, providing a useful benchmark against which numerical flow simulations can be tested. Previous simulations have, in general, been largely unsuccessful in matching the migration rate of CO2 in this layer. Here, CO2 flow within Layer 9 is modeled as a vertically-integrated gravity current that spreads beneath a structurally complex caprock using a two-dimensional grid, considerably increasing computational efficiency compared to conventional three-dimensional simulators. This flow model is inverted to find the optimal reservoir permeability in Layer 9 by minimizing the difference between observed and predicted distributions of CO2 as a function of space and time. A three parameter inverse model, comprising reservoir permeability, channel permeability and channel width, is investigated by grid search. The best-fitting reservoir permeability is 3 Darcys, which is consistent with measurements made on core material from the reservoir. Best-fitting channel permeability is 26 Darcys. Finally, the ability of this simplified numerical model

Vintage errors: do real-time economic data improve election forecasts?

Directory of Open Access Journals (Sweden)

Mark Andreas Kayser

2015-07-01

Full Text Available Economic performance is a key component of most election forecasts. When fitting models, however, most forecasters unwittingly assume that the actual state of the economy, a state best estimated by the multiple periodic revisions to official macroeconomic statistics, drives voter behavior. The difference in macroeconomic estimates between revised and original data vintages can be substantial, commonly over 100% (two-fold for economic growth estimates, making the choice of which data release to use important for the predictive validity of a model. We systematically compare the predictions of four forecasting models for numerous US presidential elections using real-time and vintage data. We find that newer data are not better data for election forecasting: forecasting error increases with data revisions. This result suggests that voter perceptions of economic growth are influenced more by media reports about the economy, which are based on initial economic estimates, than by the actual state of the economy.

Short-range forecast of Shershnevskoie (South Ural) water-storage algal blooms: preliminary results of predictors' choosing and membership functions' construction

Science.gov (United States)

Gayazova, Anna; Abdullaev, Sanjar

2014-05-01

Short-range forecasting of algal blooms in drinking water reservoirs and other waterbodies is an actual element of water treatment system. Particularly, Shershnevskoie reservoir - the source of drinking water for Chelyabinsk city (South Ural region of Russia) - is exposed to interannual, seasonal and short-range fluctuations of blue-green alga Aphanizomenon flos-aquae and other dominant species abundance, which lead to technological problems and economic costs and adversely affect the water treatment quality. Whereas the composition, intensity and the period of blooms affected not only by meteorological seasonal conditions but also by ecological specificity of waterbody, that's important to develop object-oriented forecasting, particularly, search for an optimal number of predictors for such forecasting. Thereby, firstly fuzzy logic and fuzzy artificial neural network patterns for blue-green alga Microcystis aeruginosa (M. aeruginosa) blooms prediction in nearby undrained Smolino lake were developed. These results subsequently served as the base to derive membership functions for Shernevskoie reservoir forecasting patterns. Time series with the total lenght about 138-159 days of dominant species seasonal abundance, water temperature, cloud cover, wind speed, mineralization, phosphate and nitrate concentrations were obtained through field observations held at Lake Smolino (Chelyabinsk) in the warm season of 2009 and 2011 with time resolution of 2-7 days. The cross-correlation analysis of the data revealed the potential predictors of M. aeruginosa abundance quasi-periodic oscillations: green alga Pediastrum duplex (P. duplex) abundance and mineralization for 2009, P. duplex abundance, water temperature and concentration of nitrates for 2011. According to the results of cross-correlation analysis one membership function "P. duplex abundance" and one rule linking M. aeruginosa and P. duplex abundances were set up for database of 2009. Analogically, for database of 2011

Effects of water-supply reservoirs on streamflow in Massachusetts

Science.gov (United States)

Levin, Sara B.

2016-10-06

State and local water-resource managers need modeling tools to help them manage and protect water-supply resources for both human consumption and ecological needs. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a decision-support tool to estimate the effects of reservoirs on natural streamflow. The Massachusetts Reservoir Simulation Tool is a model that simulates the daily water balance of a reservoir. The reservoir simulation tool provides estimates of daily outflows from reservoirs and compares the frequency, duration, and magnitude of the volume of outflows from reservoirs with estimates of the unaltered streamflow that would occur if no dam were present. This tool will help environmental managers understand the complex interactions and tradeoffs between water withdrawals, reservoir operational practices, and reservoir outflows needed for aquatic habitats.A sensitivity analysis of the daily water balance equation was performed to identify physical and operational features of reservoirs that could have the greatest effect on reservoir outflows. For the purpose of this report, uncontrolled releases of water (spills or spillage) over the reservoir spillway were considered to be a proxy for reservoir outflows directly below the dam. The ratio of average withdrawals to the average inflows had the largest effect on spillage patterns, with the highest withdrawals leading to the lowest spillage. The size of the surface area relative to the drainage area of the reservoir also had an effect on spillage; reservoirs with large surface areas have high evaporation rates during the summer, which can contribute to frequent and long periods without spillage, even in the absence of water withdrawals. Other reservoir characteristics, such as variability of inflows, groundwater interactions, and seasonal demand patterns, had low to moderate effects on the frequency, duration, and magnitude of spillage. The

Numerical Simulations of Spread Characteristics of Toxic Cyanide in the Danjiangkou Reservoir in China under the Effects of Dam Cooperation

Directory of Open Access Journals (Sweden)

Libin Chen

2014-01-01

Full Text Available Many accidents of releasing toxic pollutants into surface water happen each year in the world. It is believed that dam cooperation can affect flow field in reservoir and then can be applied to avoiding and reducing spread speed of toxic pollutants to drinking water intake mouth. However, few studies investigated the effects of dam cooperation on the spread characteristics of toxic pollutants in reservoir, especially the source reservoir for water diversion with more than one dam. The Danjiangkou Reservoir is the source reservoir of the China’ South-to-North Water Diversion Middle Route Project. The human activities are active within this reservoir basin and cyanide-releasing accident once happened in upstream inflow. In order to simulate the spread characteristics of cyanide in the reservoir in the condition of dam cooperation, a three-dimensional water quality model based on the Environmental Fluid Dynamics Code (EFDC has been built and put into practice. The results indicated that cooperation of two dams of the Danjiangkou Reservoir could be applied to avoiding and reducing the spread speed of toxic cyanide in the reservoir directing to the water intake mouth for water diversions.

APPLICATION OF INTEGRATED RESERVOIR MANAGEMENT AND RESERVOIR CHARACTERIZATION

Energy Technology Data Exchange (ETDEWEB)

Jack Bergeron; Tom Blasingame; Louis Doublet; Mohan Kelkar; George Freeman; Jeff Callard; David Moore; David Davies; Richard Vessell; Brian Pregger; Bill Dixon; Bryce Bezant

2000-03-01

Reservoir performance and characterization are vital parameters during the development phase of a project. Infill drilling of wells on a uniform spacing, without regard to characterization does not optimize development because it fails to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, especially carbonate reservoirs. These reservoirs are typically characterized by: (1) large, discontinuous pay intervals; (2) vertical and lateral changes in reservoir properties; (3) low reservoir energy; (4) high residual oil saturation; and (5) low recovery efficiency. The operational problems they encounter in these types of reservoirs include: (1) poor or inadequate completions and stimulations; (2) early water breakthrough; (3) poor reservoir sweep efficiency in contacting oil throughout the reservoir as well as in the nearby well regions; (4) channeling of injected fluids due to preferential fracturing caused by excessive injection rates; and (5) limited data availability and poor data quality. Infill drilling operations only need target areas of the reservoir which will be economically successful. If the most productive areas of a reservoir can be accurately identified by combining the results of geological, petrophysical, reservoir performance, and pressure transient analyses, then this ''integrated'' approach can be used to optimize reservoir performance during secondary and tertiary recovery operations without resorting to ''blanket'' infill drilling methods. New and emerging technologies such as geostatistical modeling, rock typing, and rigorous decline type curve analysis can be used to quantify reservoir quality and the degree of interwell communication. These results can then be used to develop a 3-D simulation model for prediction of infill locations. The application of reservoir surveillance techniques to identify additional reservoir ''pay'' zones

Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

Energy Technology Data Exchange (ETDEWEB)

D. O. Hitzman; A. K. Stepp; D. M. Dennis; L. R. Graumann

2003-03-31

This research program is directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal is to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. Experimental laboratory work is underway. Microbial cultures have been isolated from produced water samples. Comparative laboratory studies demonstrating in situ production of microbial products as oil recovery agents were conducted in sand packs with natural field waters with cultures and conditions representative of oil reservoirs. Field pilot studies are underway.

Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM

Directory of Open Access Journals (Sweden)

Nobuaki Kimura

2014-01-01

Full Text Available Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS, which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present, 2015 - 2039 (Near-future, and 2075 - 2099 (Future, provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM. Ten extreme rainfall (top ten events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present and 0.9 - 2.2 (Future/Present, respectively. Additionally, we evaluated how these future discharges would affect the reservoir¡¦s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam¡¦s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir¡¦s flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.

Integrating geologic and engineering data into 3-D reservoir models: an example from norman wells field, NWT, Canada

International Nuclear Information System (INIS)

Yose, L.A.

2004-01-01

A case study of the Norman Wells field will be presented to highlight the work-flow and data integration steps associated with characterization and modeling of a complex hydrocarbon reservoir. Norman Wells is a Devonian-age carbonate bank ('reef') located in the Northwest Territories of Canada, 60 kilometers south of the Arctic Circle. The reservoir reaches a maximum thickness of 130 meters in the reef interior and thins toward the basin due to depositional pinch outs. Norman Wells is an oil reservoir and is currently under a 5-spot water injection scheme for enhanced oil recovery (EOR). EOR strategies require a detailed understanding of how reservoir flow units, flow barriers and flow baffles are distributed to optimize hydrocarbon sweep and recovery and to minimize water handling. Reservoir models are routinely used by industry to characterize the 3-D distribution of reservoir architecture (stratigraphic layers, depositional facies, faults) and rock properties (porosity. permeability). Reservoir models are validated by matching historical performance data (e.g., reservoir pressures, well production or injection rates). Geologic models are adjusted until they produce a history match, and model adjustments are focused on inputs that have the greatest geologic uncertainty. Flow simulation models are then used to optimize field development strategies and to forecast field performance under different development scenarios. (author)

Assessing Seasonal Climate Forecasts over Africa to Support Decision-Making : Bridging Science and Policy Implication for Managing Climate Extremes

NARCIS (Netherlands)

Wanders, Niko|info:eu-repo/dai/nl/364253940; Wood, Eric F.

2018-01-01

Recent drought events like in the 2011 Horn of Africa and the ongoing drought in California have an enormous impact on nature and society. Reliable seasonal weather outlooks are critical for drought management and other applications like, crop modelling, flood forecasting and planning of reservoir

Survival Estimates for the Passage of Juvenile Chinook Salmon through Snake River Dams and Reservoirs, 1993 Annual Report.

Energy Technology Data Exchange (ETDEWEB)

Iwamoto, Robert N.; Sandford, Benjamin P.; McIntyre, Kenneth W.

1994-04-01

A pilot study was conducted to estimate survival of hatchery-reared yearling chinook salmon through dams and reservoirs on the Snake River. The goals of the study were to: (1) field test and evaluate the Single-Release, Modified-Single-Release, and Paired-Release Models for the estimation of survival probabilities through sections of a river and hydroelectric projects; (2) identify operational and logistical constraints to the execution of these models; and (3) determine the usefulness of the models in providing estimates of survival probabilities. Field testing indicated that the numbers of hatchery-reared yearling chinook salmon needed for accurate survival estimates could be collected at different areas with available gear and methods. For the primary evaluation, seven replicates of 830 to 1,442 hatchery-reared yearling chinook salmon were purse-seined from Lower Granite Reservoir, PIT tagged, and released near Nisqually John boat landing (River Kilometer 726). Secondary releases of PIT-tagged smolts were made at Lower Granite Dam to estimate survival of fish passing through turbines and after detection in the bypass system. Similar secondary releases were made at Little Goose Dam, but with additional releases through the spillway. Based on the success of the 1993 pilot study, the authors believe that the Single-Release and Paired-Release Models will provide accurate estimates of juvenile salmonid passage survival for individual river sections, reservoirs, and hydroelectric projects in the Columbia and Snake Rivers.

Survival estimates for the passage of juvenile chinook salmon through Snake River dams and reservoirs. Annual report 1993

International Nuclear Information System (INIS)

Iwamoto, R.N.; Muir, W.D.; Sandford, B.P.; McIntyre, K.W.; Frost, D.A.; Williams, J.G.; Smith, S.G.; Skalski, J.R.

1994-04-01

A pilot study was conducted to estimate survival of hatchery-reared yearling chinook salmon through dams and reservoirs on the Snake River. The goals of the study were to: (1) field test and evaluate the Single-Release, Modified-Single-Release, and Paired-Release Models for the estimation of survival probabilities through sections of a river and hydroelectric projects; (2) identify operational and logistical constraints to the execution of these models; and (3) determine the usefulness of the models in providing estimates of survival probabilities. Field testing indicated that the numbers of hatchery-reared yearling chinook salmon needed for accurate survival estimates could be collected at different areas with available gear and methods. For the primary evaluation, seven replicates of 830 to 1,442 hatchery-reared yearling chinook salmon were purse-seined from Lower Granite Reservoir, PIT tagged, and released near Nisqually John boat landing (River Kilometer 726). Secondary releases of PIT-tagged smolts were made at Lower Granite Dam to estimate survival of fish passing through turbines and after detection in the bypass system. Similar secondary releases were made at Little Goose Dam, but with additional releases through the spillway. Based on the success of the 1993 pilot study, the authors believe that the Single-Release and Paired-Release Models will provide accurate estimates of juvenile salmonid passage survival for individual river sections, reservoirs, and hydroelectric projects in the Columbia and Snake Rivers

Web3DGIS-Based System for Reservoir Landslide Monitoring and Early Warning

OpenAIRE

Huang Huang; Jianhua Ni; Yu Zhang; Tianlu Qian; Dingtao Shen; Jiechen Wang

2016-01-01

Landslides are the most frequent type of natural disaster, and they bring about large-scale damage and are a threat to human lives and infrastructure; therefore, the ability to conduct real-time monitoring and early warning is important. In this study, a Web3DGIS (Web3D geographic information systems) system for monitoring and forecasting landslides was developed using the Danjiangkou Reservoir area as a case study. The development of this technique involved system construction, functional de...

[Characteristics of dissolved organic carbon release under inundation from typical grass plants in the water-level fluctuation zone of the Three Gorges Reservoir area].

Science.gov (United States)

Tan, Qiu-Xia; Zhu, Boi; Hua, Ke-Ke

2013-08-01

The water-level fluctuation zone of the Three Gorges Reservoir (TGR) exposes in spring and summer, then, green plants especially herbaceous plants grow vigorously. In the late of September, water-level fluctuation zone of TGR goes to inundation. Meanwhile, annually accumulated biomass of plant will be submerged for decaying, resulting in organism decomposition and release a large amount of dissolved organic carbon (DOC). This may lead to negative impacts on water environment of TGR. The typical herbaceous plants from water-level fluctuation zone were collected and inundated in the laboratory for dynamic measurements of DOC concentration of overlying water. According to the determination, the DOC release rates and fluxes have been calculated. Results showed that the release process of DOC variation fitted in a parabolic curve. The peak DOC concentrations emerge averagely in the 15th day of inundation, indicating that DOC released quickly with organism decay of herbaceous plant. The release process of DOC could be described by the logarithm equation. There are significant differences between the concentration of DOC (the maximum DOC concentration is 486.88 mg x L(-1) +/- 35.97 mg x L(-1) for Centaurea picris, the minimum is 4.18 mg x L(-1) +/- 1.07 mg x L(-1) for Echinochloacrus galli) and the release amount of DOC (the maximum is 50.54 mg x g(-1) for Centaurea picris, the minimum is 6.51 mg x g(-1) for Polygonum hydropiper) due to different characteristics of plants, especially, the values of C/N of herbaceous plants. The cumulative DOC release quantities during the whole inundation period were significantly correlated with plants' C/N values in linear equations.

Reservoir characterization of Pennsylvanian sandstone reservoirs. Final report

Energy Technology Data Exchange (ETDEWEB)

Kelkar, M.

1995-02-01

This final report summarizes the progress during the three years of a project on Reservoir Characterization of Pennsylvanian Sandstone Reservoirs. The report is divided into three sections: (i) reservoir description; (ii) scale-up procedures; (iii) outcrop investigation. The first section describes the methods by which a reservoir can be described in three dimensions. The next step in reservoir description is to scale up reservoir properties for flow simulation. The second section addresses the issue of scale-up of reservoir properties once the spatial descriptions of properties are created. The last section describes the investigation of an outcrop.

Evaluations of Extended-Range tropical Cyclone Forecasts in the Western North Pacific by using the Ensemble Reforecasts: Preliminary Results

Science.gov (United States)

Tsai, Hsiao-Chung; Chen, Pang-Cheng; Elsberry, Russell L.

2017-04-01

The objective of this study is to evaluate the predictability of the extended-range forecasts of tropical cyclone (TC) in the western North Pacific using reforecasts from National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) during 1996-2015, and from the Climate Forecast System (CFS) during 1999-2010. Tsai and Elsberry have demonstrated that an opportunity exists to support hydrological operations by using the extended-range TC formation and track forecasts in the western North Pacific from the ECMWF 32-day ensemble. To demonstrate this potential for the decision-making processes regarding water resource management and hydrological operation in Taiwan reservoir watershed areas, special attention is given to the skill of the NCEP GEFS and CFS models in predicting the TCs affecting the Taiwan area. The first objective of this study is to analyze the skill of NCEP GEFS and CFS TC forecasts and quantify the forecast uncertainties via verifications of categorical binary forecasts and probabilistic forecasts. The second objective is to investigate the relationships among the large-scale environmental factors [e.g., El Niño Southern Oscillation (ENSO), Madden-Julian Oscillation (MJO), etc.] and the model forecast errors by using the reforecasts. Preliminary results are indicating that the skill of the TC activity forecasts based on the raw forecasts can be further improved if the model biases are minimized by utilizing these reforecasts.

Research of processes of eutrophication of Teteriv river reservoir based on neural networks mass

Directory of Open Access Journals (Sweden)

Yelnikova T.A.

2016-12-01

Full Text Available Methods of process control of eutrophication in water are based on water sampling, handling them in the laboratory and calculation of indexes of pond ecosystem. However, these methods have some significant drawbacks associated with using manual labor. The method of determining of the geometric parameters of phytoplankton through the use of neural networks for processing water samples is developed. Due to this method eutrophic processes of reservoirs of river Teteriv are investigated. A comparative analysis of eutrophic processes of reservoirs "Denyshi" and “Vidsichne” intake during 2014-2015 years are given. The differences between qualitative and quantitative composition of phytoplankton algae in two reservoirs of the river Teteriv used for water supply of Zhitomir city area are found out. The influence of exogenous and endogenous factors on the expansion of phytoplankton is researched. Research results can be used for monitoring and forecasting of ecological state of water for household purposes, used for water supply of cities.

Rapid reservoir erosion, hyperconcentrated flow, and downstream deposition triggered by breaching of 38 m tall Condit Dam, White Salmon River, Washington

Science.gov (United States)

Wilcox, Andrew C.; O'Connor, James E.; Major, Jon J.

2014-01-01

Condit Dam on the White Salmon River, Washington, a 38 m high dam impounding a large volume (1.8 million m3) of fine-grained sediment (60% sand, 35% silt and clay, and 5% gravel), was rapidly breached in October 2011. This unique dam decommissioning produced dramatic upstream and downstream geomorphic responses in the hours and weeks following breaching. Blasting a 5 m wide hole into the base of the dam resulted in rapid reservoir drawdown, abruptly releasing ~1.6 million m3 of reservoir water, exposing reservoir sediment to erosion, and triggering mass failures of the thickly accumulated reservoir sediment. Within 90 min of breaching, the reservoir's water and ~10% of its sediment had evacuated. At a gauging station 2.3 km downstream, flow increased briefly by 400 m3 s−1during passage of the initial pulse of released reservoir water, followed by a highly concentrated flow phase—up to 32% sediment by volume—as landslide-generated slurries from the reservoir moved downstream. This hyperconcentrated flow, analogous to those following volcanic eruptions or large landslides, draped the downstream river with predominantly fine sand. During the ensuing weeks, suspended-sediment concentration declined and sand and gravel bed load derived from continued reservoir erosion aggraded the channel by >1 m at the gauging station, after which the river incised back to near its initial elevation at this site. Within 15 weeks after breaching, over 1 million m3 of suspended load is estimated to have passed the gauging station, consistent with estimates that >60% of the reservoir's sediment had eroded. This dam removal highlights the influence of interactions among reservoir erosion processes, sediment composition, and style of decommissioning on rate of reservoir erosion and consequent downstream behavior of released sediment.

Modeling the Effects of Reservoir Releases on the Bed Material Sediment Flux of the Colorado River in western Colorado and eastern Utah

Science.gov (United States)

Pitlick, J.; Bizzi, S.; Schmitt, R. J. P.

2017-12-01

Warm-water reaches of the upper Colorado River have historically provided important habitat for four endangered fishes. Over time these habitats have been altered or lost due to reductions in peak flows and sediment loads caused by reservoir operations. In an effort to reverse these trends, controlled reservoir releases are now used to enhance sediment transport and restore channel complexity. In this presentation, we discuss the development of a sediment routing model designed to assess how changes in water and sediment supply can affect the mass balance of sediment. The model is formulated for ten reaches of the Colorado River spanning 250 km where values of bankfull discharge, width, and reach-average slope have been measured. Bed surface grain size distributions (GSDs) have also been measured throughout the study area; these distributions are used as a test of the model, not as input, except as an upstream boundary condition. In modeling fluxes and GSDs, we assume that the bed load transport capacity is determined by local hydraulic conditions and bed surface grain sizes. Estimates of the bankfull bed load transport capacity in each reach are computed for 14 size fractions of the surface bed material, and the fractional transport rates are summed to get the total transport capacity. In the adjacent reach, fluxes of each size fraction from upstream are used to determine the mean grain size, and the fractional transport capacity of that reach. Calculations proceed downstream and illustrate how linked changes in discharge, shear stress and mean grain size affect (1) the total bed load transport capacity, and (2) the size distribution of the bed surface sediment. The results show that model-derived GSDs match measured GSDs very closely, except for two reaches in the lower part of the study area where slope is affected by uplift associated with salt diapirs; here the model significantly overestimates the transport capacity in relation to the supply. Except for these

Survival estimates for the passage of juvenile salmonids through Snake River dams and reservoirs, 1996. Annual report

International Nuclear Information System (INIS)

Smith, S.G.; Muir, W.D.; Hockersmith, E.E.; Achord, S.; Eppard, M.B.; Ruehle, T.E.; Williams, J.G.

1998-02-01

In 1996, the National Marine Fisheries Service and the University of Washington completed the fourth year of a multi-year study to estimate survival of juvenile salmonids (Oncorhynchus spp.) passing through dams and reservoirs on the Snake River. Actively migrating smolts were collected near the head of Lower Granite Reservoir and at Lower Granite Dam, tagged with passive integrated transponder (PIT) tags, and released to continue their downstream migration. Individual smolts were subsequently detected at PIT-tag detection facilities at Lower Granite, Little Goose, Lower Monumental, McNary, John Day and Bonneville Dams. Survival estimates were calculated using the Single-Release (SR) and Paired-Release (PR) Models. Timing of releases of tagged hatchery steelhead (O. mykiss) from the head of Lower Granite Reservoir and yearling chinook salmon (O. tshawytscha) from Lower Granite Dam in 1996 spanned the major portion of their juvenile migrations. Specific research objectives in 1996 were to (1) estimate reach and project survival in the Snake River using the Single-Release and Paired-Release Models throughout the yearling chinook salmon and steelhead migrations, (2) evaluate the performance of the survival-estimation models under prevailing operational and environmental conditions in the Snake River, and (3) synthesize results from the 4 years of the study to investigate relationships between survival probabilities, travel times, and environmental factors such as flow levels and water temperature

Survival Estimates for the Passage of Juvenile Salmonids through Snake River Dams and Reservoirs, 1996 Annual Report

Energy Technology Data Exchange (ETDEWEB)

Smith, Steven G.

1998-02-01

In 1996, the National Marine Fisheries Service and the University of Washington completed the fourth year of a multi-year study to estimate survival of juvenile salmonids (Oncorhynchus spp.) passing through dams and reservoirs on the Snake River. Actively migrating smolts were collected near the head of Lower Granite Reservoir and at Lower Granite Dam, tagged with passive integrated transponder (PIT) tags, and released to continue their downstream migration. Individual smolts were subsequently detected at PIT-tag detection facilities at Lower Granite, Little Goose, Lower Monumental, McNary, John Day and Bonneville Dams. Survival estimates were calculated using the Single-Release (SR) and Paired-Release (PR) Models. Timing of releases of tagged hatchery steelhead (O. mykiss) from the head of Lower Granite Reservoir and yearling chinook salmon (O. tshawytscha) from Lower Granite Dam in 1996 spanned the major portion of their juvenile migrations. Specific research objectives in 1996 were to (1) estimate reach and project survival in the Snake River using the Single-Release and Paired-Release Models throughout the yearling chinook salmon and steelhead migrations, (2) evaluate the performance of the survival-estimation models under prevailing operational and environmental conditions in the Snake River, and (3) synthesize results from the 4 years of the study to investigate relationships between survival probabilities, travel times, and environmental factors such as flow levels and water temperature.

Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

Science.gov (United States)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

2017-11-01

Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias

House Price Forecasts, Forecaster Herding, and the Recent Crisis

DEFF Research Database (Denmark)

Stadtmann, Georg; Pierdzioch; Ruelke

2013-01-01

We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

Environmental hedging: A theory and method for reconciling reservoir operations for downstream ecology and water supply

Science.gov (United States)

Adams, L. E.; Lund, J. R.; Moyle, P. B.; Quiñones, R. M.; Herman, J. D.; O'Rear, T. A.

2017-09-01

Building reservoir release schedules to manage engineered river systems can involve costly trade-offs between storing and releasing water. As a result, the design of release schedules requires metrics that quantify the benefit and damages created by releases to the downstream ecosystem. Such metrics should support making operational decisions under uncertain hydrologic conditions, including drought and flood seasons. This study addresses this need and develops a reservoir operation rule structure and method to maximize downstream environmental benefit while meeting human water demands. The result is a general approach for hedging downstream environmental objectives. A multistage stochastic mixed-integer nonlinear program with Markov Chains, identifies optimal "environmental hedging," releases to maximize environmental benefits subject to probabilistic seasonal hydrologic conditions, current, past, and future environmental demand, human water supply needs, infrastructure limitations, population dynamics, drought storage protection, and the river's carrying capacity. Environmental hedging "hedges bets" for drought by reducing releases for fish, sometimes intentionally killing some fish early to reduce the likelihood of large fish kills and storage crises later. This approach is applied to Folsom reservoir in California to support survival of fall-run Chinook salmon in the lower American River for a range of carryover and initial storage cases. Benefit is measured in terms of fish survival; maintaining self-sustaining native fish populations is a significant indicator of ecosystem function. Environmental hedging meets human demand and outperforms other operating rules, including the current Folsom operating strategy, based on metrics of fish extirpation and water supply reliability.

House Price Forecasts, Forecaster Herding, and the Recent Crisis

Directory of Open Access Journals (Sweden)

Christian Pierdzioch

2012-11-01

Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

The role of predictive uncertainty in the operational management of reservoirs

Directory of Open Access Journals (Sweden)

E. Todini

2014-09-01

Full Text Available The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc. or via stochastic (generally stochastic dynamic programming approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

Future reservoir management under climate change for the Mississippi River

International Nuclear Information System (INIS)

Asnaashari, Ahmad; Gharabaghi, Bahram; McBean, Edward A.; Kunjikutty, Sobhalatha; Lehman, Paul; Wade, Winston

2010-01-01

This paper is part of an ongoing research project designed to evaluate the effect of climate change on reservoir operation policies in the Mississippi Valley Conservation Authority. The study used the results from a first paper, including projected daily temperature and precipitation, for future streamflow calculation. This paper presented the development, calibration and validation of a rainfall-runoff NAM model for the Mississippi River watershed. The calibrated Mike11/NAM model was fed with predicted climatic data to generate long term future streamflow in the basin. Forecast flows were run in a Mike 11/HD model to estimate the corresponding lake levels. The storages and flows at Shabomeka Lake, Mazinaw Lake and Marble Lake were simulated. The results showed that climate change is likely to have implications for reservoir operations in the Mississippi River watershed, which will include changed water level regimes due to modifications in the projected future streamflow hydrograph to meet desired lake levels.

Development of a management tool for reservoirs in Mediterranean environments based on uncertainty analysis

Science.gov (United States)

Gómez-Beas, R.; Moñino, A.; Polo, M. J.

2012-05-01

In compliance with the development of the Water Framework Directive, there is a need for an integrated management of water resources, which involves the elaboration of reservoir management models. These models should include the operational and technical aspects which allow us to forecast an optimal management in the short term, besides the factors that may affect the volume of water stored in the medium and long term. The climate fluctuations of the water cycle that affect the reservoir watershed should be considered, as well as the social and economic aspects of the area. This paper shows the development of a management model for Rules reservoir (southern Spain), through which the water supply is regulated based on set criteria, in a sustainable way with existing commitments downstream, with the supply capacity being well established depending on demand, and the probability of failure when the operating requirements are not fulfilled. The results obtained allowed us: to find out the reservoir response at different time scales, to introduce an uncertainty analysis and to demonstrate the potential of the methodology proposed here as a tool for decision making.

Model of medicines sales forecasting taking into account factors of influence

Science.gov (United States)

Kravets, A. G.; Al-Gunaid, M. A.; Loshmanov, V. I.; Rasulov, S. S.; Lempert, L. B.

2018-05-01

The article describes a method for forecasting sales of medicines in conditions of data sampling, which is insufficient for building a model based on historical data alone. The developed method is applicable mainly to new drugs that are already licensed and released for sale but do not yet have stable sales performance in the market. The purpose of this study is to prove the effectiveness of the suggested method forecasting drug sales, taking into account the selected factors of influence, revealed during the review of existing solutions and analysis of the specificity of the area under study. Three experiments were performed on samples of different volumes, which showed an improvement in the accuracy of forecasting sales in small samples.

Simulation and optimisation modelling approach for operation of the Hoa Binh Reservoir, Vietnam

DEFF Research Database (Denmark)

Ngo, Long le; Madsen, Henrik; Rosbjerg, Dan

2007-01-01

Hoa Binh, the largest reservoir in Vietnam, plays an important role in flood control for the Red River delta and hydropower generation. Due to its multi-purpose character, conflicts and disputes in operating the reservoir have been ongoing since its construction, particularly in the flood season....... This paper proposes to optimise the control strategies for the Hoa Binh reservoir operation by applying a combination of simulation and optimisation models. The control strategies are set up in the MIKE 11 simulation model to guide the releases of the reservoir system according to the current storage level......, the hydro-meteorological conditions, and the time of the year. A heuristic global optimisation tool, the shuffled complex evolution (SCE) algorithm, is adopted for optimising the reservoir operation. The optimisation puts focus on the trade-off between flood control and hydropower generation for the Hoa...

Diffuser Operations at Spring Hollow Reservoir

OpenAIRE

Gantzer, Paul Anthony

2002-01-01

Stratification is a natural occurrence in deep lakes and reservoirs. This phenomenon results in two distinct layers, the warmer, less dense epilimnion on top and the colder, denser, hypolimnion on the bottom. The epilimnion remains saturated with dissolved oxygen (DO) from mass transfer with the atmosphere, while the hypolimnion continues to undergo oxygen-depleting processes. During seasons of high oxygen demand the hypolimnion often becomes anoxic and results in the release of compounds,...

Evaluation of induced seismicity forecast models in the Induced Seismicity Test Bench

Science.gov (United States)

Király, Eszter; Gischig, Valentin; Zechar, Jeremy; Doetsch, Joseph; Karvounis, Dimitrios; Wiemer, Stefan

2016-04-01

Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. Here, we propose an Induced Seismicity Test Bench to test and rank such models. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models that incorporate a different mix of physical understanding and stochastic representation of the induced sequences: Shapiro in Space (SiS) and Hydraulics and Seismics (HySei). SiS is based on three pillars: the seismicity rate is computed with help of the seismogenic index and a simple exponential decay of the seismicity; the magnitude distribution follows the Gutenberg-Richter relation; and seismicity is distributed in space based on smoothing seismicity during the learning period with 3D Gaussian kernels. The HySei model describes seismicity triggered by pressure diffusion with irreversible permeability enhancement. Our results show that neither model is fully superior to the other. HySei forecasts the seismicity rate well, but is only mediocre at forecasting the spatial distribution. On the other hand, SiS forecasts the spatial distribution well but not the seismicity rate. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in. Ensemble models that combine HySei's rate forecast with SiS's spatial forecast outperform each individual model.

Comparison of static and dynamic resilience for a multipurpose reservoir operation

Science.gov (United States)

Simonovic, Slobodan P.; Arunkumar, R.

2016-11-01

Reliability, resilience, and vulnerability are the traditional risk measures used to assess the performance of a reservoir system. Among these measures, resilience is used to assess the ability of a reservoir system to recover from a failure event. However, the time-independent static resilience does not consider the system characteristics, interaction of various individual components and does not provide much insight into reservoir performance from the beginning of the failure event until the full performance recovery. Knowledge of dynamic reservoir behavior under the disturbance offers opportunities for proactive and/or reactive adaptive response that can be selected to maximize reservoir resilience. A novel measure is required to provide insight into the dynamics of reservoir performance based on the reservoir system characteristics and its adaptive capacity. The reservoir system characteristics include, among others, reservoir storage curve, reservoir inflow, reservoir outflow capacity, and reservoir operating rules. The reservoir adaptive capacity can be expressed using various impacts of reservoir performance under the disturbance (like reservoir release for meeting a particular demand, socioeconomic consequences of reservoir performance, or resulting environmental state of the river upstream and downstream from the reservoir). Another way of expressing reservoir adaptive capacity to a disturbing event may include aggregated measures like reservoir robustness, redundancy, resourcefulness, and rapidity. A novel measure that combines reservoir performance and its adaptive capacity is proposed in this paper and named "dynamic resilience." The paper also proposes a generic simulation methodology for quantifying reservoir resilience as a function of time. The proposed resilience measure is applied to a single multipurpose reservoir operation and tested for a set of failure scenarios. The dynamic behavior of reservoir resilience is captured using the system

Bathymetry and capacity of Shawnee Reservoir, Oklahoma, 2016

Science.gov (United States)

Ashworth, Chad E.; Smith, S. Jerrod; Smith, Kevin A.

2017-02-13

Shawnee Reservoir (locally known as Shawnee Twin Lakes) is a man-made reservoir on South Deer Creek with a drainage area of 32.7 square miles in Pottawatomie County, Oklahoma. The reservoir consists of two lakes connected by an equilibrium channel. The southern lake (Shawnee City Lake Number 1) was impounded in 1935, and the northern lake (Shawnee City Lake Number 2) was impounded in 1960. Shawnee Reservoir serves as a municipal water supply, and water is transferred about 9 miles by gravity to a water treatment plant in Shawnee, Oklahoma. Secondary uses of the reservoir are for recreation, fish and wildlife habitat, and flood control. Shawnee Reservoir has a normal-pool elevation of 1,069.0 feet (ft) above North American Vertical Datum of 1988 (NAVD 88). The auxiliary spillway, which defines the flood-pool elevation, is at an elevation of 1,075.0 ft.The U.S. Geological Survey (USGS), in cooperation with the City of Shawnee, has operated a real-time stage (water-surface elevation) gage (USGS station 07241600) at Shawnee Reservoir since 2006. For the period of record ending in 2016, this gage recorded a maximum stage of 1,078.1 ft on May 24, 2015, and a minimum stage of 1,059.1 ft on April 10–11, 2007. This gage did not report reservoir storage prior to this report (2016) because a sufficiently detailed and thoroughly documented bathymetric (reservoir-bottom elevation) survey and corresponding stage-storage relation had not been published. A 2011 bathymetric survey with contours delineated at 5-foot intervals was published in Oklahoma Water Resources Board (2016), but that publication did not include a stage-storage relation table. The USGS, in cooperation with the City of Shawnee, performed a bathymetric survey of Shawnee Reservoir in 2016 and released the bathymetric-survey data in 2017. The purposes of the bathymetric survey were to (1) develop a detailed bathymetric map of the reservoir and (2) determine the relations between stage and reservoir storage

Mathematical modeling of pollutant and radionuclide transformation in aquatic ecosystems results of elaboration and verification for the chain of industrial reservoirs on the Techa River

International Nuclear Information System (INIS)

Smirnov, A.B.; Mokrov, Y.G.; Glagolenko, Y.V.; Drozhko, E.G.; Khodakovsky, I.L.; Leonov, A.V.

1995-01-01

The modern radioecological situation around the oldest radiochemical plant, Mayak, in South Ural (Russia) is indicated by the storage of 300 million to tons of low level radioactive waste in the Techa's reservoir chain (TRC). Future approaches for TRC restoration may be evaluated using corresponding mathematical models. The mathematical modeling complex, KASKAD, was developed at Mayak and is intended for reservoir radioecological state forecasting and alternative remediation approaches evaluation. The paper describes this model

Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

Energy Technology Data Exchange (ETDEWEB)

Hitzman, D.O.; Stepp, A.K.; Dennis, D.M.; Graumann, L.R.

2003-02-11

This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents.

International Aftershock Forecasting: Lessons from the Gorkha Earthquake

Science.gov (United States)

Michael, A. J.; Blanpied, M. L.; Brady, S. R.; van der Elst, N.; Hardebeck, J.; Mayberry, G. C.; Page, M. T.; Smoczyk, G. M.; Wein, A. M.

2015-12-01

Following the M7.8 Gorhka, Nepal, earthquake of April 25, 2015 the USGS issued a series of aftershock forecasts. The initial impetus for these forecasts was a request from the USAID Office of US Foreign Disaster Assistance to support their Disaster Assistance Response Team (DART) which coordinated US Government disaster response, including search and rescue, with the Government of Nepal. Because of the possible utility of the forecasts to people in the region and other response teams, the USGS released these forecasts publicly through the USGS Earthquake Program web site. The initial forecast used the Reasenberg and Jones (Science, 1989) model with generic parameters developed for active deep continental regions based on the Garcia et al. (BSSA, 2012) tectonic regionalization. These were then updated to reflect a lower productivity and higher decay rate based on the observed aftershocks, although relying on teleseismic observations, with a high magnitude-of-completeness, limited the amount of data. After the 12 May M7.3 aftershock, the forecasts used an Epidemic Type Aftershock Sequence model to better characterize the multiple sources of earthquake clustering. This model provided better estimates of aftershock uncertainty. These forecast messages were crafted based on lessons learned from the Christchurch earthquake along with input from the U.S. Embassy staff in Kathmandu. Challenges included how to balance simple messaging with forecasts over a variety of time periods (week, month, and year), whether to characterize probabilities with words such as those suggested by the IPCC (IPCC, 2010), how to word the messages in a way that would translate accurately into Nepali and not alarm the public, and how to present the probabilities of unlikely but possible large and potentially damaging aftershocks, such as the M7.3 event, which had an estimated probability of only 1-in-200 for the week in which it occurred.

Hybrid Multi-Objective Optimization of Folsom Reservoir Operation to Maximize Storage in Whole Watershed

Science.gov (United States)

Goharian, E.; Gailey, R.; Maples, S.; Azizipour, M.; Sandoval Solis, S.; Fogg, G. E.

2017-12-01

The drought incidents and growing water scarcity in California have a profound effect on human, agricultural, and environmental water needs. California experienced multi-year droughts, which have caused groundwater overdraft and dropping groundwater levels, and dwindling of major reservoirs. These concerns call for a stringent evaluation of future water resources sustainability and security in the state. To answer to this call, Sustainable Groundwater Management Act (SGMA) was passed in 2014 to promise a sustainable groundwater management in California by 2042. SGMA refers to managed aquifer recharge (MAR) as a key management option, especially in areas with high variation in water availability intra- and inter-annually, to secure the refill of underground water storage and return of groundwater quality to a desirable condition. The hybrid optimization of an integrated water resources system provides an opportunity to adapt surface reservoir operations for enhancement in groundwater recharge. Here, to re-operate Folsom Reservoir, objectives are maximizing the storage in the whole American-Cosumnes watershed and maximizing hydropower generation from Folsom Reservoir. While a linear programing (LP) module tends to maximize the total groundwater recharge by distributing and spreading water over suitable lands in basin, a genetic based algorithm, Non-dominated Sorting Genetic Algorithm II (NSGA-II), layer above it controls releases from the reservoir to secure the hydropower generation, carry-over storage in reservoir, available water for replenishment, and downstream water requirements. The preliminary results show additional releases from the reservoir for groundwater recharge during high flow seasons. Moreover, tradeoffs between the objectives describe that new operation performs satisfactorily to increase the storage in the basin, with nonsignificant effects on other objectives.

Flood forecasting and uncertainty of precipitation forecasts

International Nuclear Information System (INIS)

Kobold, Mira; Suselj, Kay

2004-01-01

The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

Numerical Weather Forecasting at the Savannah River Site

International Nuclear Information System (INIS)

Buckley, R.L.

1999-01-01

Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations

How seasonal forecast could help a decision maker: an example of climate service for water resource management

Science.gov (United States)

Viel, Christian; Beaulant, Anne-Lise; Soubeyroux, Jean-Michel; Céron, Jean-Pierre

2016-04-01

The FP7 project EUPORIAS was a great opportunity for the climate community to co-design with stakeholders some original and innovative climate services at seasonal time scales. In this framework, Météo-France proposed a prototype that aimed to provide to water resource managers some tailored information to better anticipate the coming season. It is based on a forecasting system, built on a refined hydrological suite, forced by a coupled seasonal forecast model. It particularly delivers probabilistic river flow prediction on river basins all over the French territory. This paper presents the work we have done with "EPTB Seine Grands Lacs" (EPTB SGL), an institutional stakeholder in charge of the management of 4 great reservoirs on the upper Seine Basin. First, we present the co-design phase, which means the translation of classical climate outputs into several indices, relevant to influence the stakeholder's decision making process (DMP). And second, we detail the evaluation of the impact of the forecast on the DMP. This evaluation is based on an experiment realised in collaboration with the stakeholder. Concretely EPTB SGL has replayed some past decisions, in three different contexts: without any forecast, with a forecast A and with a forecast B. One of forecast A and B really contained seasonal forecast, the other only contained random forecasts taken from past climate. This placebo experiment, realised in a blind test, allowed us to calculate promising skill scores of the DMP based on seasonal forecast in comparison to a classical approach based on climatology, and to EPTG SGL current practice.

Reservoir Engineering Optimization Strategies for Subsurface CO{sub 2} Storage

Energy Technology Data Exchange (ETDEWEB)

Mclntire, Blayde; McPherson, Brian

2013-09-30

The purpose of this report is to outline a methodology for calculating the optimum number of injection wells for geologic CCS. The methodology is intended primarily for reservoir pressure management, and factors in cost as well. Efficiency may come in many forms depending on project goals; therefore, various results are presented simultaneously. The developed methodology is illustrated via application in a case study of the Rocky Mountain Carbon Capture and Storage (RMCCS) project, including a CCS candidate site near Craig, Colorado, USA. The forecasting method provided reasonable estimates of cost and injection volume when compared to simulated results.

Scenario approach for the seasonal forecast of Kharif flows from the Upper Indus Basin

Science.gov (United States)

Fraz Ismail, Muhammad; Bogacki, Wolfgang

2018-02-01

Snow and glacial melt runoff are the major sources of water contribution from the high mountainous terrain of the Indus River upstream of the Tarbela reservoir. A reliable forecast of seasonal water availability for the Kharif cropping season (April-September) can pave the way towards better water management and a subsequent boost in the agro-economy of Pakistan. The use of degree-day models in conjunction with satellite-based remote-sensing data for the forecasting of seasonal snow and ice melt runoff has proved to be a suitable approach for data-scarce regions. In the present research, the Snowmelt Runoff Model (SRM) has not only been enhanced by incorporating the glacier (G) component but also applied for the forecast of seasonal water availability from the Upper Indus Basin (UIB). Excel-based SRM+G takes account of separate degree-day factors for snow and glacier melt processes. All-year simulation runs with SRM+G for the period 2003-2014 result in an average flow component distribution of 53, 21, and 26 % for snow, glacier, and rain, respectively. The UIB has been divided into Upper and Lower parts because of the different climatic conditions in the Tibetan Plateau. The scenario approach for seasonal forecasting, which like the Ensemble Streamflow Prediction method uses historic meteorology as model forcings, has proven to be adequate for long-term water availability forecasts. The accuracy of the forecast with a mean absolute percentage error (MAPE) of 9.5 % could be slightly improved compared to two existing operational forecasts for the UIB, and the bias could be reduced to -2.0 %. However, the association between forecasts and observations as well as the skill in predicting extreme conditions is rather weak for all three models, which motivates further research on the selection of a subset of ensemble members according to forecasted seasonal anomalies.

Intelligent monitoring system for real-time geologic CO2 storage, optimization and reservoir managemen

Science.gov (United States)

Dou, S.; Commer, M.; Ajo Franklin, J. B.; Freifeld, B. M.; Robertson, M.; Wood, T.; McDonald, S.

2017-12-01

Archer Daniels Midland Company's (ADM) world-scale agricultural processing and biofuels production complex located in Decatur, Illinois, is host to two industrial-scale carbon capture and storage projects. The first operation within the Illinois Basin-Decatur Project (IBDP) is a large-scale pilot that injected 1,000,000 metric tons of CO2 over a three year period (2011-2014) in order to validate the Illinois Basin's capacity to permanently store CO2. Injection for the second operation, the Illinois Industrial Carbon Capture and Storage Project (ICCS), started in April 2017, with the purpose of demonstrating the integration of carbon capture and storage (CCS) technology at an ethanol plant. The capacity to store over 1,000,000 metric tons of CO2 per year is anticipated. The latter project is accompanied by the development of an intelligent monitoring system (IMS) that will, among other tasks, perform hydrogeophysical joint analysis of pressure, temperature and seismic reflection data. Using a preliminary radial model assumption, we carry out synthetic joint inversion studies of these data combinations. We validate the history-matching process to be applied to field data once CO2-breakthrough at observation wells occurs. This process will aid the estimation of permeability and porosity for a reservoir model that best matches monitoring observations. The reservoir model will further be used for forecasting studies in order to evaluate different leakage scenarios and develop appropriate early-warning mechanisms. Both the inversion and forecasting studies aim at building an IMS that will use the seismic and pressure-temperature data feeds for providing continuous model calibration and reservoir status updates.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

Science.gov (United States)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Natural and industrial analogues for release of CO2 from storagereservoirs: Identification of features, events, and processes and lessonslearned

Energy Technology Data Exchange (ETDEWEB)

Lewicki, Jennifer L.; Birkholzer, Jens; Tsang, Chin-Fu

2006-03-03

The injection and storage of anthropogenic CO{sub 2} in deep geologic formations is a potentially feasible strategy to reduce CO{sub 2} emissions and atmospheric concentrations. While the purpose of geologic carbon storage is to trap CO{sub 2} underground, CO{sub 2} could migrate away from the storage site into the shallow subsurface and atmosphere if permeable pathways such as well bores or faults are present. Large-magnitude releases of CO{sub 2} have occurred naturally from geologic reservoirs in numerous volcanic, geothermal, and sedimentary basin settings. Carbon dioxide and natural gas have also been released from geologic CO{sub 2} reservoirs and natural gas storage facilities, respectively, due to influences such as well defects and injection/withdrawal processes. These systems serve as natural and industrial analogues for the potential release of CO{sub 2} from geologic storage reservoirs and provide important information about the key features, events, and processes (FEPs) that are associated with releases, as well as the health, safety, and environmental consequences of releases and mitigation efforts that can be applied. We describe a range of natural releases of CO{sub 2} and industrial releases of CO{sub 2} and natural gas in the context of these characteristics. Based on this analysis, several key conclusions can be drawn, and lessons can be learned for geologic carbon storage. First, CO{sub 2} can both accumulate beneath, and be released from, primary and secondary reservoirs with capping units located at a wide range of depths. Both primary and secondary reservoir entrapments for CO{sub 2} should therefore be well characterized at storage sites. Second, many natural releases of CO{sub 2} have been correlated with a specific event that triggered the release, such as magmatic fluid intrusion or seismic activity. The potential for processes that could cause geomechanical damage to sealing cap rocks and trigger the release of CO{sub 2} from a storage

Gas deliverability forecasting - why bother?

International Nuclear Information System (INIS)

Trick, M.

1996-01-01

According to the author the answer to the question is an unequivocal 'yes' because gas production forecasting is extremely useful for the management and development of a gas field. To model a gas field, one must take into account reservoir performance, sandface inflow performance, wellbore pressure losses, gathering system pressure losses, and field facility performance. The integration of all these factors in a single computer-based model that incorporates proven technology will facilitate the evaluation of various development strategies. A good computer model can help to predict the most cost effective improvement methods, determine economic viability, estimate how much gas is available, evaluate whether drilling wells or adding compression will produce the most reserves, determine optimum placement of compression, evaluate changes to the gathering system, and determine if production from existing wells can be increased by wellbore modifications

Scientific rationale for antiretroviral therapy in 2005: viral reservoirs and resistance evolution.

Science.gov (United States)

Siliciano, Robert F

2005-01-01

Hope for a cure for HIV-1 infection was dampened by the discovery of a latent form of the virus that persists in resting CD4+ cells. This reservoir of latently HIV-infected resting memory T cells represents an archive of viral genotypes produced in an individual from the onset of infection. Entry into the reservoir is stopped with suppressive antiretroviral therapy, but the archived viruses are capable of re-initiating active infections, are released continuously from this reservoir, and can cause viral rebound if antiretroviral therapy is stopped. Studies of residual low-level viremia (Robert F. Siliciano, MD, PhD, at the International AIDS Society-USA course in New York in March 2005.

Design of a lube oil reservoir by using flow calculations

Energy Technology Data Exchange (ETDEWEB)

Rinkinen, J; Alfthan, A. [Institute of Hydraulics and Automation IHA, Tampere University of Technology, Tampere (Finland)] Suominen, J. [Institute of Energy and Process Engineering, Tampere University of Technology, Tampere (Finland); Airaksinen, A; Antila, K [R and D Engineer Safematic Oy, Muurame (Finland)

1998-12-31

The volume of usual oil reservoir for lubrication oil systems is designed by the traditional rule of thumb so that the total oil volume is theoretically changed in every 30 minutes by rated pumping capacity. This is commonly used settling time for air, water and particles to separate by gravity from the oil returning of the bearings. This leads to rather big volumes of lube oil reservoirs, which are sometimes difficult to situate in different applications. In this presentation traditionally sized lube oil reservoir (8 m{sup 3}) is modelled in rectangular coordinates and laminar oil flow is calculated by using FLUENT software that is based on finite difference method. The results of calculation are velocity and temperature fields inside the reservoir. The velocity field is used to visualize different particle paths through the reservoir. Particles that are studied by the model are air bubbles and water droplets. The interest of the study has been to define the size of the air bubbles that are released and the size of the water droplets that are separated in the reservoir. The velocity field is also used to calculate the modelled circulating time of the oil volume which is then compared with the theoretical circulating time that is obtained from the rated pump flow. These results have been used for designing a new lube oil reservoir. This reservoir has also been modelled and optimized by the aid of flow calculations. The best shape of the designed reservoir is constructed in real size for empirical measurements. Some results of the oil flow measurements are shown. (orig.) 7 refs.

Design of a lube oil reservoir by using flow calculations

Energy Technology Data Exchange (ETDEWEB)

Rinkinen, J.; Alfthan, A. [Institute of Hydraulics and Automation IHA, Tampere University of Technology, Tampere (Finland)] Suominen, J. [Institute of Energy and Process Engineering, Tampere University of Technology, Tampere (Finland); Airaksinen, A.; Antila, K. [R and D Engineer Safematic Oy, Muurame (Finland)

1997-12-31

The volume of usual oil reservoir for lubrication oil systems is designed by the traditional rule of thumb so that the total oil volume is theoretically changed in every 30 minutes by rated pumping capacity. This is commonly used settling time for air, water and particles to separate by gravity from the oil returning of the bearings. This leads to rather big volumes of lube oil reservoirs, which are sometimes difficult to situate in different applications. In this presentation traditionally sized lube oil reservoir (8 m{sup 3}) is modelled in rectangular coordinates and laminar oil flow is calculated by using FLUENT software that is based on finite difference method. The results of calculation are velocity and temperature fields inside the reservoir. The velocity field is used to visualize different particle paths through the reservoir. Particles that are studied by the model are air bubbles and water droplets. The interest of the study has been to define the size of the air bubbles that are released and the size of the water droplets that are separated in the reservoir. The velocity field is also used to calculate the modelled circulating time of the oil volume which is then compared with the theoretical circulating time that is obtained from the rated pump flow. These results have been used for designing a new lube oil reservoir. This reservoir has also been modelled and optimized by the aid of flow calculations. The best shape of the designed reservoir is constructed in real size for empirical measurements. Some results of the oil flow measurements are shown. (orig.) 7 refs.

Long-term generation scheduling of Xiluodu and Xiangjiaba cascade hydro plants considering monthly streamflow forecasting error

International Nuclear Information System (INIS)

Xie, Mengfei; Zhou, Jianzhong; Li, Chunlong; Zhu, Shuang

2015-01-01

Highlights: • Monthly streamflow forecasting error is considered. • An improved parallel progressive optimality algorithm is proposed. • Forecasting dispatching chart is manufactured accompanying with a set of rules. • Applications in Xiluodu and Xiangjiaba cascade hydro plants. - Abstract: Reliable streamflow forecasts are very significant for reservoir operation and hydropower generation. But for monthly streamflow forecasting, the forecasting result is unreliable and it is hard to be utilized, although it has a certain reference value for long-term hydro generation scheduling. Current researches mainly focus on deterministic scheduling, and few of them consider the uncertainties. So this paper considers the forecasting error which exists in monthly streamflow forecasting and proposes a new long-term hydro generation scheduling method called forecasting dispatching chart for Xiluodu and Xiangjiaba cascade hydro plants. First, in order to consider the uncertainties of inflow, Monte Carlo simulation is employed to generate streamflow data according to the forecasting value and error distribution curves. Then the large amount of data obtained by Monte Carlo simulation is used as inputs for long-term hydro generation scheduling model. Because of the large amount of streamflow data, the computation speed of conventional algorithm cannot meet the demand. So an improved parallel progressive optimality algorithm is proposed to solve the long-term hydro generation scheduling problem and a series of solutions are obtained. These solutions constitute an interval set, unlike the unique solution in the traditional deterministic long-term hydro generation scheduling. At last, the confidence intervals of the solutions are calculated and forecasting dispatching chart is proposed as a new method for long-term hydro generation scheduling. A set of rules are proposed corresponding to forecasting dispatching chart. The chart is tested for practical operations and achieves

The mechanics of shallow magma reservoir outgassing

Science.gov (United States)

Parmigiani, A.; Degruyter, W.; Leclaire, S.; Huber, C.; Bachmann, O.

2017-08-01

Magma degassing fundamentally controls the Earth's volatile cycles. The large amount of gas expelled into the atmosphere during volcanic eruptions (i.e., volcanic outgassing) is the most obvious display of magmatic volatile release. However, owing to the large intrusive:extrusive ratio, and considering the paucity of volatiles left in intrusive rocks after final solidification, volcanic outgassing likely constitutes only a small fraction of the overall mass of magmatic volatiles released to the Earth's surface. Therefore, as most magmas stall on their way to the surface, outgassing of uneruptible, crystal-rich magma storage regions will play a dominant role in closing the balance of volatile element cycling between the mantle and the surface. We use a numerical approach to study the migration of a magmatic volatile phase (MVP) in crystal-rich magma bodies ("mush zones") at the pore scale. Our results suggest that buoyancy-driven outgassing is efficient over crystal volume fractions between 0.4 and 0.7 (for mm-sized crystals). We parameterize our pore-scale results for MVP migration in a thermomechanical magma reservoir model to study outgassing under dynamical conditions where cooling controls the evolution of the proportion of crystal, gas, and melt phases and to investigate the role of the reservoir size and the temperature-dependent viscoelastic response of the crust on outgassing efficiency. We find that buoyancy-driven outgassing allows for a maximum of 40-50% volatiles to leave the reservoir over the 0.4-0.7 crystal volume fractions, implying that a significant amount of outgassing must occur at high crystal content (>0.7) through veining and/or capillary fracturing.

Correcting underestimation of optimal fracture length by modeling proppant conductivity variations in hydraulically fractured gas/condensate reservoirs

Energy Technology Data Exchange (ETDEWEB)

Akram, A.H.; Samad, A. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Schlumberger, Houston, TX (United States)

2006-07-01

A study was conducted in which a newly developed numerical simulator was used to forecast the productivity of a hydraulically fractured well in a retrograde gas-condensate sandstone reservoir. The effect of condensate dropout was modeled in both the reservoir and the proppant pack. The type of proppant and the stress applied to it are among the factors that determine proppant conductivity in a single-phase flow. Other factors include the high velocity of gas and the presence of liquid in the proppant pack. It was concluded that apparent proppant permeability in a gas condensate reservoir varies along the length of the hydraulic fracture and depends on the distance from the wellbore. It will increase towards the tip of the fracture where liquid ratio and velocity are lower. Apparent proppant permeability also changes with time. Forecasting is most accurate when these conditions are considered in the simulation. There are 2 problems associated with the use of a constant proppant permeability in a gas condensate reservoir. The first relates to the fact that it is impossible to obtain a correct single number that will mimic the drawdown of the real fracture at a particular rate without going through the process of determining the proppant permeability profile in a numerical simulator. The second problem relates to the fact that constant proppant permeability yields an optimal fracture length that is too short. Analytical modeling does not account for these complexities. It was determined that the only way to accurately simulate the behaviour of a hydraulic fracture in a high rate well, is by advanced numerical modeling that considers varying apparent proppant permeability in terms of time and distance along the fracture length. 10 refs., 2 tabs., 16 figs., 1 appendix.

Remedial investigation/feasibility study report for Lower Watts Bar Reservoir Operable Unit

International Nuclear Information System (INIS)

1995-03-01

This document is the combined Remedial Investigation and Feasibility Study Report for the lower Watts Bar Reservoir (LWBR) Operable Unit (OU). The LWBR is located in Roane, Rhea, and Meigs counties, Tennessee, and consists of Watts Bar Reservoir downstream of the Clinch river. This area has received hazardous substances released over a period of 50 years from the US Department of Energy's Oak Ridge Reservation (ORR), a National Priority List site established under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). As required by this law, the ORR and all off-site areas that have received contaminants, including LWBR, must be investigated to determine the risk to human health and the environment resulting from these releases, the need for any remedial action to reduce these risks, and the remedial actions that are most feasible for implementation in this OU. Contaminants from the ORR are primarily transported to the LWBR via the Clinch River. There is little data regarding the quantities of most contaminants potentially released from the ORR to the Clinch River, particularly for the early years of ORR operations. Estimates of the quantities released during this period are available for most radionuclides and some inorganic contaminants, indicating that releases 30 to 50 years ago were much higher than today. Since the early 1970s, the release of potential contaminants has been monitored for compliance with environmental law and reported in the annual environmental monitoring reports for the ORR

Remedial investigation/feasibility study report for Lower Watts Bar Reservoir Operable Unit

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-03-01

This document is the combined Remedial Investigation and Feasibility Study Report for the lower Watts Bar Reservoir (LWBR) Operable Unit (OU). The LWBR is located in Roane, Rhea, and Meigs counties, Tennessee, and consists of Watts Bar Reservoir downstream of the Clinch river. This area has received hazardous substances released over a period of 50 years from the US Department of Energy`s Oak Ridge Reservation (ORR), a National Priority List site established under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). As required by this law, the ORR and all off-site areas that have received contaminants, including LWBR, must be investigated to determine the risk to human health and the environment resulting from these releases, the need for any remedial action to reduce these risks, and the remedial actions that are most feasible for implementation in this OU. Contaminants from the ORR are primarily transported to the LWBR via the Clinch River. There is little data regarding the quantities of most contaminants potentially released from the ORR to the Clinch River, particularly for the early years of ORR operations. Estimates of the quantities released during this period are available for most radionuclides and some inorganic contaminants, indicating that releases 30 to 50 years ago were much higher than today. Since the early 1970s, the release of potential contaminants has been monitored for compliance with environmental law and reported in the annual environmental monitoring reports for the ORR.

A unique application of the instream flow incremental methodology (IFIM) to predict impacts on riverine aquatic habitat, resulting from construction of a proposed hydropower reservoir

International Nuclear Information System (INIS)

Foote, P.S.

1999-01-01

The City of Harrisburg, Pennsylvania, proposed to construct a new low-head hydroelectric project on the Susquehanna River in the central part of the state in 1986, about 108 km upstream of the river mouth. As part of the licensing process, the city was required by the Federal Energy Regulatory Commission to carry out studies that would forecast the impacts on riverine aquatic habitat as a result of construction of the proposed 13 km long by 1.5 km wide reservoir. The methodology selected by the city and its consultants was to use the IFIM to model the habitat conditions in the project reach both before and after construction of the proposed reservoir.The IFIM is usually used to model instream flow releases downstream of dams and diversions, and had not been used before to model habitat conditions within the proposed reservoir area. The study team hydraulically modelled the project reach using existing hydraulic data, and a HEC-2 backwater analysis to determine post-project water surface elevations. The IFG-4 model was used to simulate both pre- and post-project water velocities, by distributing velocities across transects based on known discharges and cell depth. Effects on aquatic habitat were determined using the IFIM PHABSIM program, in which criteria for several evaluation species and life stages were used to yield estimates of Weighted Usable Area. The analysis showed, based on trends in WUA from pre- and post-project conditions, that habitat conditions would improve for several species and life stages, and would be negatively affected for fewer life stages and species. Some agency concerns that construction of the proposed reservoir would have significant adverse effects on the resident and anadromous fish populations were responded to using these results

Forecast Combinations

OpenAIRE

Timmermann, Allan G

2005-01-01

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

Variability in perceived satisfaction of reservoir management objectives

Science.gov (United States)

Owen, W.J.; Gates, T.K.; Flug, M.

1997-01-01

Fuzzy set theory provides a useful model to address imprecision in interpreting linguistically described objectives for reservoir management. Fuzzy membership functions can be used to represent degrees of objective satisfaction for different values of management variables. However, lack of background information, differing experiences and qualifications, and complex interactions of influencing factors can contribute to significant variability among membership functions derived from surveys of multiple experts. In the present study, probabilistic membership functions are used to model variability in experts' perceptions of satisfaction of objectives for hydropower generation, fish habitat, kayaking, rafting, and scenery preservation on the Green River through operations of Flaming Gorge Dam. Degree of variability in experts' perceptions differed among objectives but resulted in substantial uncertainty in estimation of optimal reservoir releases.

Forecaster Behaviour and Bias in Macroeconomic Forecasts

OpenAIRE

Roy Batchelor

2007-01-01

This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

Advancing reservoir operation description in physically based hydrological models

Science.gov (United States)

Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

2016-04-01

Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

Forecast combinations

OpenAIRE

Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

2010-01-01

We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

Selection of reservoirs amenable to micellar flooding. First annual report, October 1978-December 1979

Energy Technology Data Exchange (ETDEWEB)

Goldburg, A.; Price, H.

1980-12-01

The overall project objective is to build a solid engineering base upon which the Department of Energy (DOE) can improve and accelerate the application of micellar-polymer recovery technology to Mid-Continent and California sandstone reservoirs. The purpose of the work carried out under these two contracts is to significantly aid, both DOE and the private sector, in gaining the following Project Objectives: to select the better micellar-polymer prospects in the Mid-Continent and California regions; to assess all of the available field and laboratory data which has a bearing on recovering oil by micellar-polymer projects in order to help identify and resolve both the technical and economic constraints relating thereto; and to design and analyze improved field pilots and tests and to develop a micellar-polymer applications matrix for use by the potential technology users; i.e., owner/operators. The report includes the following: executive summary and project objectives; development of a predictive model for economic evaluation of reservoirs; reservoir data bank for micellar-polymer recovery evaluation; PECON program for preliminary economic evaluation; ordering of candidate reservoirs for additional data acquisition; validation of predictive model by numerical simulation; and work forecast. Tables, figures and references are included.

Uncertainty in forecasting breakthrough of fluid transported through fractures

International Nuclear Information System (INIS)

Horne, R.N.

1989-01-01

Tracer experiments in geothermal reservoirs emphasize the very great variability in rates of fluid movement through fractured rocks. This variability extends from the 10-meter to the kilometer-length scale. Thus tracer returns have been observed at some locations within hours at distances of up to 1 kilometer from the injection point, while other much nearer locations in the same formation do not observe the tracer until much later. In addition, transport rates have sometimes been extremely fast (up to 100 m/hr) even over such distances. This paper discusses the conclusions reached after compiling the results of a large number of tracer tests in several different fractured reservoirs. It is evident in some cases that large-scale geological features, such as faults, are responsible for the variations in tracer return time. In other cases, there is no clear physical description that explains the differences. These results suggest that there will be no a priori way of forecasting transport rates in fractured systems without performing a tracer test

Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling

Directory of Open Access Journals (Sweden)

Chien-Lin Huang

2015-01-01

Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.

Remedial investigation/feasibility study report for lower Watts Bar Reservoir Operable Unit

International Nuclear Information System (INIS)

1994-08-01

This document is the combined Remedial Investigation and Feasibility Study Report for the Lower Watts Bar Reservoir (LWBR) Operable Unit (OU). The LWBR is located in Roane, Rhea, and Meigs counties, Tennessee, and consists of Watts Bar Reservoir downstream of the Clinch River. This area has received hazardous substances released over a period of 50 years from the U.S. Department of Energy's Oak Ridge Reservation (ORR), a National Priority List site established under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). As required by this law, the ORR and all off-site areas that have received containments, including LWBR, must be investigated to determine the risk to human health and the environment resulting from these releases, the need for any remedial action to reduce these risks, and the remedial actions that are most feasible for implementation in this OU. Contaminants from the ORR are primarily transported to the LWBR via the Clinch River. Water-soluble contaminants released to ORR surface waters are rapidly diluted upon entering the Clinch River and then quickly transported downstream to the Tennessee River where further dilution occurs. Almost the entire quantity of these diluted contaminants rapidly flows through LWBR. In contrast, particle-associated contaminants tend to accumulate in the lower Clinch River and in LWBR in areas of sediment deposition. Those particle-associated contaminants that were released in peak quantities during the early years of ORR operations (e.g., mercury and 137 Cs) are buried under as much as 80 cm of cleaner sediment in LWBR. Certain contaminants, most notably polychlorinated biphenyls (PCBs), have accumulated in LWBR biota. The contamination of aquatic biota with PCBs is best documented for certain fish species and extends to reservoirs upstream of the ORR, indicating a contamination problem that is regional in scope and not specific to the ORR

Bulk and Surface Aqueous Speciation of Calcite: Implications for Low-Salinity Waterflooding of Carbonate Reservoirs

KAUST Repository

Yutkin, Maxim P.

2017-08-25

calcite bulk and surface equilibria draws several important inferences about the proposed LSW oil-recovery mechanisms. Diffuse double-layer expansion (DLE) is impossible for brine ionic strength greater than 0.1 molar. Because of rapid rock/brine equilibration, the dissolution mechanism for releasing adhered oil is eliminated. Also, fines mobilization and concomitant oil release cannot occur because there are few loose fines and clays in a majority of carbonates. LSW cannot be a low-interfacial-tension alkaline flood because carbonate dissolution exhausts all injected base near the wellbore and lowers pH to that set by the rock and by formation CO2. In spite of diffuse double-layer collapse in carbonate reservoirs, surface ion-exchange oil release remains feasible, but unproved.

Modeling the Transport and Fate of Fecal Pollution and Nutrients of Miyun Reservoir

Science.gov (United States)

Liu, L.; Fu, X.; Wang, G.

2009-12-01

Miyun Reservoir, a mountain valley reservoir, is located 100 km northeast of Beijing City. Besides the functions of flood control, irrigation and fishery for Beijing area, Miyun Reservoir is the main drinking water storage for Beijing city. The water quality is therefore of great importance. Recently, the concentration of fecal pollution and nutrients in the reservoir are constantly rising to arrest the attention of Beijing municipality. Fecal pollution from sewage is a significant public health concern due to the known presence of human viruses and parasites in these discharges. To investigate the transport and fate of the fecal pollution and nutrients at Miyun reservoir and the health risks associated with drinking and fishery, the reservoir and two tributaries, Chaohe river and Baihe river discharging into it are being examined for bacterial, nutrients and other routine pollution. To understand the relative importance of different processes influencing pollution transport and inactivation, a finite-element model of surf-zone hydrodynamics (coupled with models for temperature, fecal pollution, nutrients and other routine contaminants) is used. The developed models are being verified by the observed water quality data including water temperature, conductivities and dissolved oxygen from the reservoir and its tributaries. Different factors impacting the inactivation of fecal pollution and the transport of nutrients such as water temperature, sedimentation, sunlight insolation are evaluated for Miyun reservoir by a sensitivity analysis analogized from the previous research of Lake Michigan (figure 1, indicating that solar insolation dominates the inactivation of E. Coli, an indicator of fecal pollution, Liu et al. 2006). The calibrated modeling system can be used to temporally and spatially simulate and predict the variation of the concentration of fecal pollution and nutrients of Miyun reservoir. Therefore this research can provide a forecasting tool for the

Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

Science.gov (United States)

Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

2016-12-01

Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

Mesoscale Modeling, Forecasting and Remote Sensing Research.

Science.gov (United States)

remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

Short-term wind power combined forecasting based on error forecast correction

International Nuclear Information System (INIS)

Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

2016-01-01

Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

Fortescue reservoir development and reservoir studies

Energy Technology Data Exchange (ETDEWEB)

Henzell, S.T.; Hicks, G.J.; Horden, M.J.; Irrgang, H.R.; Janssen, E.J.; Kable, C.W.; Mitchell, R.A.H.; Morrell, N.W.; Palmer, I.D.; Seage, N.W.

1985-03-01

The Fortescue field in the Gippsland Basin, offshore southeastern Australia is being developed from two platforms (Fortescue A and Cobia A) by Esso Australia Ltd. (operator) and BHP Petroleum. The Fortescue reservoir is a stratigraphic trap at the top of the Latrobe Group of sediments. It overlies the western flank of the Halibut and Cobia fields and is separated from them by a non-net sequence of shales and coals which form a hydraulic barrier between the two systems. Development drilling into the Fortescue reservoir commenced in April 1983 with production coming onstream in May 1983. Fortescue, with booked reserves of 44 stock tank gigalitres (280 million stock tank barrels) of 43/sup 0/ API oil, is the seventh major oil reservoir to be developed in the offshore Gippsland Basin by Esso/BHP. In mid-1984, after drilling a total of 20 exploration and development wells, and after approximately one year of production, a detailed three-dimensional, two-phase reservoir simulation study was performed to examine the recovery efficiency, drainage patterns, pressure performance and production rate potential of the reservoir. The model was validated by history matching an extensive suite of Repeat Formation Test (RFT) pressure data. The results confirmed the reserves basis, and demonstrated that the ultimate oil recovery from the reservoir is not sensitive to production rate. This result is consistent with studies on other high quality Latrobe Group reservoirs in the Gippsland Basin which contain undersaturated crudes and receive very strong water drive from the Basin-wide aquifer system. With the development of the simulation model during the development phase, it has been possible to more accurately define the optimal well pattern for the remainder of the development.

Initial assessment of a multi-model approach to spring flood forecasting in Sweden

Science.gov (United States)

Olsson, J.; Uvo, C. B.; Foster, K.; Yang, W.

2015-06-01

Hydropower is a major energy source in Sweden and proper reservoir management prior to the spring flood onset is crucial for optimal production. This requires useful forecasts of the accumulated discharge in the spring flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialised set-up of the HBV model. In this study, a number of new approaches to spring flood forecasting, that reflect the latest developments with respect to analysis and modelling on seasonal time scales, are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for three main Swedish rivers over a 10-year period with lead times between 0 and 4 months. In the first approach, historically analogue years with respect to the climate in the period preceding the spring flood are identified and used to compose a reduced ensemble. In the second, seasonal meteorological ensemble forecasts are used to drive the HBV model over the spring flood period. In the third approach, statistical relationships between SFV and the large-sale atmospheric circulation are used to build forecast models. None of the new approaches consistently outperform the climatological ensemble approach, but for specific locations and lead times improvements of 20-30 % are found. When combining all forecasts in a weighted multi-model approach, a mean improvement over all locations and lead times of nearly 10 % was indicated. This demonstrates the potential of the approach and further development and optimisation into an operational system is ongoing.

Application of reservoir characterization and advanced technology to improve recovery and economics in a lower quality shallow shelf carbonate reservoir. End of budget period report, August 3, 1994--December 31, 1996

Energy Technology Data Exchange (ETDEWEB)

Taylor, A.R.; Hinterlong, G.; Watts, G.; Justice, J.; Brown, K.; Hickman, T.S.

1997-12-01

The Oxy West Welch project is designed to demonstrate how the use of advanced technology can improve the economics of miscible CO{sub 2} injection projects in a lower quality shallow shelf carbonate reservoir. The research and design phase primarily involves advanced reservoir characterization and accelerating the production response. The demonstration phase will implement the reservoir management plan based on an optimum miscible CO{sub 2} flood as designed in the initial phase. During Budget Period 1, work was completed on the CO{sub 2} stimulation treatments and the hydraulic fracture design. Analysis of the CO{sub 2} stimulation treatment provided a methodology for predicting results. The hydraulic fracture treatment proved up both the fracture design approach a and the use of passive seismic for mapping the fracture wing orientation. Although the 3-D seismic interpretation is still being integrated into the geologic model and interpretation of borehole seismic is still underway, the simulator has been enhanced to the point of giving good waterflood history matches. The simulator-forecasted results for an optimal designed miscible CO{sub 2} flood in the demonstration area gave sufficient economics to justify continuation of the project into Budget Period 2.

Fuel cycle forecasting - there are forecasts and there are forecasts

International Nuclear Information System (INIS)

Puechl, K.H.

1975-01-01

The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

Fuel cycle forecasting - there are forecasts and there are forecasts

Energy Technology Data Exchange (ETDEWEB)

Puechl, K H

1975-12-01

The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

Natural and human drivers of salinity in reservoirs and their implications in water supply operation through a Decision Support System

Science.gov (United States)

Contreras, Eva; Gómez-Beas, Raquel; Linares-Sáez, Antonio

2016-04-01

Salt can be a problem when is originally in aquifers or when it dissolves in groundwater and comes to the ground surface or flows into streams. The problem increases in lakes hydraulically connected with aquifers affecting water quality. This issue is even more alarming when water resources are used for urban and irrigation supply and water quantity and quality restrict that water demand. This work shows a data based and physical modeling approach in the Guadalhorce reservoir, located in southern Spain. This water body receives salt contribution from mainly groundwater flow, getting salinity values in the reservoir from 3500 to 5500 μScm-1. Moreover, Guadalhorce reservoir is part of a complex system of reservoirs fed from the Guadalhorce River that supplies all urban, irrigation, tourism, energy and ecology water uses, which makes that implementation and validation of methods and tools for smart water management is required. Meteorological, hydrological and water quality data from several monitoring networks and data sources, with both historical and real time data during a 40-years period, were used to analyze the impact salinity. On the other hand, variables that mainly depend on the dam operation, such as reservoir water level and water outflow, were also analyzed to understand how they affect to salinity in depth and time. Finally surface and groundwater inflows to the reservoir were evaluated through a physically based hydrological model to forecast when the major contributions take place. Reservoir water level and surface and groundwater inflows were found to be the main drivers of salinity in the reservoir. When reservoir water level is high, daily water inflow around 0.4 hm3 causes changes in salinity (both drop and rise) up to 500 μScm-1, but no significant changes are found when water level falls 2-3 m. However the gradual water outflows due to dam operation and consequent decrease in reservoir water levels makes that, after dry periods, salinity

Advantageous Reservoir Characterization Technology in Extra Low Permeability Oil Reservoirs

Directory of Open Access Journals (Sweden)

Yutian Luo

2017-01-01

Full Text Available This paper took extra low permeability reservoirs in Dagang Liujianfang Oilfield as an example and analyzed different types of microscopic pore structures by SEM, casting thin sections fluorescence microscope, and so on. With adoption of rate-controlled mercury penetration, NMR, and some other advanced techniques, based on evaluation parameters, namely, throat radius, volume percentage of mobile fluid, start-up pressure gradient, and clay content, the classification and assessment method of extra low permeability reservoirs was improved and the parameter boundaries of the advantageous reservoirs were established. The physical properties of reservoirs with different depth are different. Clay mineral variation range is 7.0%, and throat radius variation range is 1.81 μm, and start pressure gradient range is 0.23 MPa/m, and movable fluid percentage change range is 17.4%. The class IV reservoirs account for 9.56%, class II reservoirs account for 12.16%, and class III reservoirs account for 78.29%. According to the comparison of different development methods, class II reservoir is most suitable for waterflooding development, and class IV reservoir is most suitable for gas injection development. Taking into account the gas injection in the upper section of the reservoir, the next section of water injection development will achieve the best results.

Quantification of Interbasin Transfers into the Addicks Reservoir during Hurricane Harvey

Science.gov (United States)

Sebastian, A.; Juan, A.; Gori, A.; Maulsby, F.; Bedient, P. B.

2017-12-01

Between August 25 and 30, Hurricane Harvey dropped unprecedented rainfall over southeast Texas causing widespread flooding in the City of Houston. Water levels in the Addicks and Barker reservoirs, built in the 1940s to protect downtown Houston, exceeded previous records by approximately 2 meters. Concerns regarding structural integrity of the dams and damage to neighbourhoods in within the reservoir pool resulted in controlled releases into Buffalo Bayou, flooding an estimated 4,000 additional structures downstream of the dams. In 2016, during the Tax Day it became apparent that overflows from Cypress Creek in northern Harris County substantially contribute to water levels in Addicks. Prior to this event, little was known about the hydrodynamics of this overflow area or about the additional stress placed on Addicks and Barker reservoirs due to the volume of overflow. However, this information is critical for determining flood risk in Addicks Watershed, and ultimately Buffalo Bayou. In this study, we utilize the recently developed HEC-RAS 2D model the interbasin transfer that occurs between Cypress Creek Watershed and Addicks Reservoir to quantify the volume and rate at which water from Cypress enters the reservoir during extreme events. Ultimately, the results of this study will help inform the official hydrologic models used by HCFCD to determine reservoir operation during future storm events and better inform residents living in or above the reservoir pool about their potential flood risk.

Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

Directory of Open Access Journals (Sweden)

Jinyin Ye

2016-01-01

Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

Small reservoir effects on headwater water quality in the rural-urban fringe, Georgia Piedmont, USA

Directory of Open Access Journals (Sweden)

Dr.. Amber R. Ignatius, Geographer

2016-12-01

Full Text Available Small reservoirs are prevalent landscape features that affect the physical, chemical, and biological characteristics of headwater streams. Tens of thousands of small reservoirs, often less than a hectare in size, were constructed over the past century within the United States. While remote-sensing and geographic-mapping technologies assist in identifying and quantifying these features, their localized influence on water quality is uncertain. We report a year-long physicochemical study of nine small reservoirs (0.15–2.17 ha within the Oconee and Broad River Watersheds in the Georgia Piedmont. Study sites were selected along an urban-rural gradient with differing amounts of agricultural, forested, and developed land covers. Sites were sampled monthly for discharge and inflow/outflow water quality parameters (temperature, specific conductance, pH, dissolved oxygen, turbidity, alkalinity, total phosphorus, total nitrogen, nitrate, ammonium. While the proportion of developed land cover within watersheds had positive correlations with reservoir specific conductivity values, agricultural and forested land covers showed correlations (positive and negative, respectively with reservoir alkalinity, total nitrogen, nitrate, and specific conductivity. The majority of outflow temperatures were warmer than inflows for all land uses throughout the year, especially in the summer. Outflows had lower nitrate concentrations, but higher ammonium. The type of outflow structure was also influential; top-release dams showed higher dissolved oxygen and pH than bottom-release dams. Water quality effects were still evident 250 m below the dam, albeit reduced.

Evaluation of Ensemble Water Supply and Demands Forecasts for Water Management in the Klamath River Basin

Science.gov (United States)

Broman, D.; Gangopadhyay, S.; McGuire, M.; Wood, A.; Leady, Z.; Tansey, M. K.; Nelson, K.; Dahm, K.

2017-12-01

The Upper Klamath River Basin in south central Oregon and north central California is home to the Klamath Irrigation Project, which is operated by the Bureau of Reclamation and provides water to around 200,000 acres of agricultural lands. The project is managed in consideration of not only water deliveries to irrigators, but also wildlife refuge water demands, biological opinion requirements for Endangered Species Act (ESA) listed fish, and Tribal Trust responsibilities. Climate change has the potential to impact water management in terms of volume and timing of water and the ability to meet multiple objectives. Current operations use a spreadsheet-based decision support tool, with water supply forecasts from the National Resources Conservation Service (NRCS) and California-Nevada River Forecast Center (CNRFC). This tool is currently limited in its ability to incorporate in ensemble forecasts, which offer the potential for improved operations by quantifying forecast uncertainty. To address these limitations, this study has worked to develop a RiverWare based water resource systems model, flexible enough to use across multiple decision time-scales, from short-term operations out to long-range planning. Systems model development has been accompanied by operational system development to handle data management and multiple modeling components. Using a set of ensemble hindcasts, this study seeks to answer several questions: A) Do a new set of ensemble streamflow forecasts have additional skill beyond what?, and allow for improved decision making under changing conditions? B) Do net irrigation water requirement forecasts developed in this project to quantify agricultural demands and reservoir evaporation forecasts provide additional benefits to decision making beyond water supply forecasts? C) What benefit do ensemble forecasts have in the context of water management decisions?

Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

Science.gov (United States)

Dreher, Joseph; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian; Van Speybroeck, Kurt

2009-01-01

The National Weather Service Forecast Office in Melbourne, FL (NWS MLB) is responsible for providing meteorological support to state and county emergency management agencies across East Central Florida in the event of incidents involving the significant release of harmful chemicals, radiation, and smoke from fires and/or toxic plumes into the atmosphere. NWS MLB uses the National Oceanic and Atmospheric Administration Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to provide trajectory, concentration, and deposition guidance during such events. Accurate and timely guidance is critical for decision makers charged with protecting the health and well-being of populations at risk. Information that can describe the geographic extent of areas possibly affected by a hazardous release, as well as to indicate locations of primary concern, offer better opportunity for prompt and decisive action. In addition, forecasters at the NWS Spaceflight Meteorology Group (SMG) have expressed interest in using the HYSPLIT model to assist with Weather Flight Rules during Space Shuttle landing operations. In particular, SMG would provide low and mid-level HYSPLIT trajectory forecasts for cumulus clouds associated with smoke plumes, and high-level trajectory forecasts for thunderstorm anvils. Another potential benefit for both NWS MLB and SMG is using the HYSPLIT model concentration and deposition guidance in fog situations.

Brittleness estimation from seismic measurements in unconventional reservoirs: Application to the Barnett shale

Science.gov (United States)

Perez Altimar, Roderick

Brittleness is a key characteristic for effective reservoir stimulation and is mainly controlled by mineralogy in unconventional reservoirs. Unfortunately, there is no universally accepted means of predicting brittleness from measures made in wells or from surface seismic data. Brittleness indices (BI) are based on mineralogy, while brittleness average estimations are based on Young's modulus and Poisson's ratio. I evaluate two of the more popular brittleness estimation techniques and apply them to a Barnett Shale seismic survey in order to estimate its geomechanical properties. Using specialized logging tools such as elemental capture tool, density, and P- and S wave sonic logs calibrated to previous core descriptions and laboratory measurements, I create a survey-specific BI template in Young's modulus versus Poisson's ratio or alternatively lambdarho versus murho space. I use this template to predict BI from elastic parameters computed from surface seismic data, providing a continuous estimate of BI estimate in the Barnett Shale survey. Extracting lambdarho-murho values from microseismic event locations, I compute brittleness index from the template and find that most microsemic events occur in the more brittle part of the reservoir. My template is validated through a suite of microseismic experiments that shows most events occurring in brittle zones, fewer events in the ductile shale, and fewer events still in the limestone fracture barriers. Estimated ultimate recovery (EUR) is an estimate of the expected total production of oil and/or gas for the economic life of a well and is widely used in the evaluation of resource play reserves. In the literature it is possible to find several approaches for forecasting purposes and economic analyses. However, the extension to newer infill wells is somewhat challenging because production forecasts in unconventional reservoirs are a function of both completion effectiveness and reservoir quality. For shale gas reservoirs

Application of Integrated Reservoir Management and Reservoir Characterization to Optimize Infill Drilling

Energy Technology Data Exchange (ETDEWEB)

P. K. Pande

1998-10-29

Initial drilling of wells on a uniform spacing, without regard to reservoir performance and characterization, must become a process of the past. Such efforts do not optimize reservoir development as they fail to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, and carbonate reservoirs in particular. These reservoirs are typically characterized by: o Large, discontinuous pay intervals o Vertical and lateral changes in reservoir properties o Low reservoir energy o High residual oil saturation o Low recovery efficiency

Forecasting Housing Approvals in Australia: Do Forecasters Herd?

DEFF Research Database (Denmark)

Stadtmann, Georg; Pierdzioch; Rülke

2012-01-01

Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

The role of reservoir characterization in the reservoir management process (as reflected in the Department of Energy`s reservoir management demonstration program)

Energy Technology Data Exchange (ETDEWEB)

Fowler, M.L. [BDM-Petroleum Technologies, Bartlesville, OK (United States); Young, M.A.; Madden, M.P. [BDM-Oklahoma, Bartlesville, OK (United States)] [and others

1997-08-01

Optimum reservoir recovery and profitability result from guidance of reservoir practices provided by an effective reservoir management plan. Success in developing the best, most appropriate reservoir management plan requires knowledge and consideration of (1) the reservoir system including rocks, and rock-fluid interactions (i.e., a characterization of the reservoir) as well as wellbores and associated equipment and surface facilities; (2) the technologies available to describe, analyze, and exploit the reservoir; and (3) the business environment under which the plan will be developed and implemented. Reservoir characterization is the essential to gain needed knowledge of the reservoir for reservoir management plan building. Reservoir characterization efforts can be appropriately scaled by considering the reservoir management context under which the plan is being built. Reservoir management plans de-optimize with time as technology and the business environment change or as new reservoir information indicates the reservoir characterization models on which the current plan is based are inadequate. BDM-Oklahoma and the Department of Energy have implemented a program of reservoir management demonstrations to encourage operators with limited resources and experience to learn, implement, and disperse sound reservoir management techniques through cooperative research and development projects whose objectives are to develop reservoir management plans. In each of the three projects currently underway, careful attention to reservoir management context assures a reservoir characterization approach that is sufficient, but not in excess of what is necessary, to devise and implement an effective reservoir management plan.

Soil erosion and organic matter loss by using fallout 137Cs as tracer in Miyun reservoir valley

International Nuclear Information System (INIS)

Hua Luo; Zhang Zhigang; Li Junbo; Feng Yan; Zhao Hong; Yin Xunxiao; Zhu Fengyun

2005-01-01

Miyun reservoir is one of the important water sources for Beijing, the water quality of the reservoir is directly influenced by soil erosion. Based on measuring the 137 Cs concentrations, organic content in the soil of selected sampling sites, the authors investigated the relationship between the quality of soil erosion and organic matters. According to classificatory standards of soil erosion, the intensity of erosion in Miyun reservoir valley is light and moderate, but in some parts erosion is serious. The land use model has dramatic influence on distribution of organic matters in the soil. Unreasonable human activities could cause serious increase of organic matter runoff and soil erosion intensity. Distributions of organic matters were increased in the following order: bush land > forestry > orchard > farmland. Organic matters in the upper course were higher than in the circumference of reservoir. The simulated model suggests that there is a cubic relation between the contents of organic matters and 137 Cs concentrations (r 2 =0.9). The math model in the single sights can forecast soil erosion and changes of concentrations of organic matters in the soils, so that the chemical analysis and measurements are simplified. (authors)

Forecasting of Average Monthly River Flows in Colombia

Science.gov (United States)

Mesa, O. J.; Poveda, G.

2006-05-01

The last two decades have witnessed a marked increase in our knowledge of the causes of interannual hydroclimatic variability and our ability to make predictions. Colombia, located near the seat of the ENSO phenomenon, has been shown to experience negative (positive) anomalies in precipitation in concert with El Niño (La Niña). In general besides the Pacific Ocean, Colombia has climatic influences from the Atlantic Ocean and the Caribbean Sea through the tropical forest of the Amazon basin and the savannas of the Orinoco River, in top of the orographic and hydro-climatic effects introduced by the Andes. As in various other countries of the region, hydro-electric power contributes a large proportion (75 %) of the total electricity generation in Colombia. Also, most agriculture is rain-fed dependant, and domestic water supply relies mainly on surface waters from creeks and rivers. Besides, various vector borne tropical diseases intensify in response to rain and temperature changes. Therefore, there is a direct connection between climatic fluctuations and national and regional economies. This talk specifically presents different forecasts of average monthly stream flows for the inflow into the largest reservoir used for hydropower generation in Colombia, and illustrates the potential economic savings of such forecasts. Because of planning of the reservoir operation, the most appropriated time scale for this application is the annual to interannual. Fortunately, this corresponds to the scale at which hydroclimate variability understanding has improved significantly. Among the different possibilities we have explored: traditional statistical ARIMA models, multiple linear regression, natural and constructed analogue models, the linear inverse model, neural network models, the non-parametric regression splines (MARS) model, regime dependant Markovian models and one we termed PREBEO, which is based on spectral bands decomposition using wavelets. Most of the methods make

Forecasting freight flows

DEFF Research Database (Denmark)

Lyk-Jensen, Stéphanie

2011-01-01

Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

Drug delivery into microneedle-porated nails from nanoparticle reservoirs.

Science.gov (United States)

Chiu, Wing Sin; Belsey, Natalie A; Garrett, Natalie L; Moger, Julian; Price, Gareth J; Delgado-Charro, M Begoña; Guy, Richard H

2015-12-28

This study demonstrates the potential of polymeric nanoparticles as drug reservoirs for sustained topical drug delivery into microneedle-treated human nail. Laser scanning confocal microscopy was used to image the delivery of a fluorescent model compound from nanoparticles into the nail. A label-free imaging technique, stimulated Raman scattering microscopy, was applied, in conjunction with two-photon fluorescence imaging, to probe the disposition of nanoparticles and an associated lipophilic 'active' in a microneedle-porated nail. The results provide clear evidence that the nanoparticles function as immobile reservoirs, sequestered on the nail surface and in the microneedle-generated pores, from which the active payload can be released and diffuse laterally into the nail over an extended period of time. Copyright © 2015 Elsevier B.V. All rights reserved.

Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

Science.gov (United States)

Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

2014-05-01

Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

Robust forecast comparison

OpenAIRE

Jin, Sainan; Corradi, Valentina; Swanson, Norman

2015-01-01

Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

Predicting petrophysical properties by simultaneous inversion of seismic and reservoir engineering data

Science.gov (United States)

Mantilla, Andres Eduardo

Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization, yet usually they have the largest impact on reserves and production forecasts, and consequently on the economy of a project. The difficulty of estimating them comes from the fact that porosity and permeability may vary significantly over the reservoir volume, but can only be sampled at well locations, often using different technologies at different scales of observation. An accurate estimation of the spatial distribution of porosity and permeability is of key importance, because it translates into higher success rates in infill drilling, and fewer wells required for draining the reservoir. The purpose of this thesis is to enhance the characterization of subsurface reservoirs by improving the prediction of petrophysical properties through the combination of reservoir geophysics and reservoir engineering observations and models. To fulfill this goal, I take advantage of the influence that petrophysical properties have on seismic and production data, and formulate, implement, and demonstrate the applicability of an inversion approach that integrates seismic and production-related observations with a-priori information about porosity and permeability. Being constrained by physical models and observations, the resulting estimates are appropriate for making reservoir management decisions. I use synthetic models to test the proposed inversion approach. Results from these tests show that, because of the excellent spatial coverage of seismic data, incorporating seismic-derived attributes related to petrophysical properties can significantly improve the estimates of porosity and permeability. The results also highlight the importance of using a-priori information about the relationship between porosity and permeability. The last chapters of this thesis describe a practical application of the proposed joint inversion approach. This application includes a rock

Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

Energy Technology Data Exchange (ETDEWEB)

Hitzman, D.O.; Stepp, A.K.

2003-02-11

This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery.

Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

Energy Technology Data Exchange (ETDEWEB)

Hitzman, D.O.; Bailey, S.A.; Stepp, A.K.

2003-02-11

This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery.

FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.

Science.gov (United States)

Alomar, Miquel L; Canals, Vincent; Perez-Mora, Nicolas; Martínez-Moll, Víctor; Rosselló, Josep L

2016-01-01

Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC) has arisen as a strategic technique to design recurrent neural networks (RNNs) with simple learning capabilities. In this work, we show a new approach to implement RC systems with digital gates. The proposed method is based on the use of probabilistic computing concepts to reduce the hardware required to implement different arithmetic operations. The result is the development of a highly functional system with low hardware resources. The presented methodology is applied to chaotic time-series forecasting.

Experiments with Interaction between the National Water Model and the Reservoir System Simulation Model: A Case Study of Russian River Basin

Science.gov (United States)

Kim, J.; Johnson, L.; Cifelli, R.; Chandra, C. V.; Gochis, D.; McCreight, J. L.; Yates, D. N.; Read, L.; Flowers, T.; Cosgrove, B.

2017-12-01

NOAA National Water Center (NWC) in partnership with the National Centers for Environmental Prediction (NCEP), the National Center for Atmospheric Research (NCAR) and other academic partners have produced operational hydrologic predictions for the nation using a new National Water Model (NWM) that is based on the community WRF-Hydro modeling system since the summer of 2016 (Gochis et al., 2015). The NWM produces a variety of hydrologic analysis and prediction products, including gridded fields of soil moisture, snowpack, shallow groundwater levels, inundated area depths, evapotranspiration as well as estimates of river flow and velocity for approximately 2.7 million river reaches. Also included in the NWM are representations for more than 1,200 reservoirs which are linked into the national channel network defined by the USGS NHDPlusv2.0 hydrography dataset. Despite the unprecedented spatial and temporal coverage of the NWM, many known deficiencies exist, including the representation of lakes and reservoirs. This study addresses the implementation of a reservoir assimilation scheme through coupling of a reservoir simulation model to represent the influence of managed flows. We examine the use of the reservoir operations to dynamically update lake/reservoir storage volume states, characterize flow characteristics of river reaches flowing into and out of lakes and reservoirs, and incorporate enhanced reservoir operating rules for the reservoir model options within the NWM. Model experiments focus on a pilot reservoir domain-Lake Mendocino, CA, and its contributing watershed, the East Fork Russian River. This reservoir is modeled using United States Army Corps of Engineers (USACE) HEC-ResSim developed for application to examine forecast informed reservoir operations (FIRO) in the Russian River basin.

Dams release methane even in temperate zoned

International Nuclear Information System (INIS)

Lemarchand, F.

2010-01-01

The Wohlen lake (near Bern) is a retaining dam built 90 years ago that has undergone a campaign to measure the quantity of methane released. The campaign lasted 1 year and the result was unexpected: 0.15 g/m 2 *day which one of the highest release rates in temperate zones. This result is all the more stunning since water stays only 2 days in average in the reservoir and that the drowned area is not important. In fact the river Aar that feeds the lake is loaded with organic matter coming from humane activities: agriculture and 3 sewage plants. This organic matter decays in the lake releasing methane. (A.C.)

Forecast communication through the newspaper Part 2: perceptions of uncertainty

Science.gov (United States)

Harris, Andrew J. L.

2015-04-01

In the first part of this review, I defined the media filter and how it can operate to frame and blame the forecaster for losses incurred during an environmental disaster. In this second part, I explore the meaning and role of uncertainty when a forecast, and its basis, is communicated through the response and decision-making chain to the newspaper, especially during a rapidly evolving natural disaster which has far-reaching business, political, and societal impacts. Within the media-based communication system, there remains a fundamental disconnect of the definition of uncertainty and the interpretation of the delivered forecast between various stakeholders. The definition and use of uncertainty differs especially between scientific, media, business, and political stakeholders. This is a serious problem for the scientific community when delivering forecasts to the public though the press. As reviewed in Part 1, the media filter can result in a negative frame, which itself is a result of bias, slant, spin, and agenda setting introduced during passage of the forecast and its uncertainty through the media filter. The result is invariably one of anger and fury, which causes loss of credibility and blaming of the forecaster. Generation of a negative frame can be aided by opacity of the decision-making process that the forecast is used to support. The impact of the forecast will be determined during passage through the decision-making chain where the precautionary principle and cost-benefit analysis, for example, will likely be applied. Choice of forecast delivery format, vehicle of communication, syntax of delivery, and lack of follow-up measures can further contribute to causing the forecast and its role to be misrepresented. Follow-up measures to negative frames may include appropriately worded press releases and conferences that target forecast misrepresentation or misinterpretation in an attempt to swing the slant back in favor of the forecaster. Review of

Forecasting Skill

Science.gov (United States)

1981-01-01

for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

Advancing Reactive Tracer Methods for Measurement of Thermal Evolution in Geothermal Reservoirs: Final Report

Energy Technology Data Exchange (ETDEWEB)

Mitchell A. Plummer; Carl D. Palmer; Earl D. Mattson; Laurence C. Hull; George D. Redden

2011-07-01

The injection of cold fluids into engineered geothermal system (EGS) and conventional geothermal reservoirs may be done to help extract heat from the subsurface or to maintain pressures within the reservoir (e.g., Rose et al., 2001). As these injected fluids move along fractures, they acquire heat from the rock matrix and remove it from the reservoir as they are extracted to the surface. A consequence of such injection is the migration of a cold-fluid front through the reservoir (Figure 1) that could eventually reach the production well and result in the lowering of the temperature of the produced fluids (thermal breakthrough). Efficient operation of an EGS as well as conventional geothermal systems involving cold-fluid injection requires accurate and timely information about thermal depletion of the reservoir in response to operation. In particular, accurate predictions of the time to thermal breakthrough and subsequent rate of thermal drawdown are necessary for reservoir management, design of fracture stimulation and well drilling programs, and forecasting of economic return. A potential method for estimating migration of a cold front between an injection well and a production well is through application of reactive tracer tests, using chemical whose rate of degradation is dependent on the reservoir temperature between the two wells (e.g., Robinson 1985). With repeated tests, the rate of migration of the thermal front can be determined, and the time to thermal breakthrough calculated. While the basic theory behind the concept of thermal tracers has been understood for some time, effective application of the method has yet to be demonstrated. This report describes results of a study that used several methods to investigate application of reactive tracers to monitoring the thermal evolution of a geothermal reservoir. These methods included (1) mathematical investigation of the sensitivity of known and hypothetical reactive tracers, (2) laboratory testing of novel

Influence of Chemical, Mechanical, and Transport Processes on Wellbore Leakage from Geologic CO2 Storage Reservoirs.

Science.gov (United States)

Carroll, Susan A; Iyer, Jaisree; Walsh, Stuart D C

2017-08-15

Wells are considered to be high-risk pathways for fluid leakage from geologic CO 2 storage reservoirs, because breaches in this engineered system have the potential to connect the reservoir to groundwater resources and the atmosphere. Given these concerns, a few studies have assessed leakage risk by evaluating regulatory records, often self-reported, documenting leakage in gas fields. Leakage is thought to be governed largely by initial well-construction quality and the method of well abandonment. The geologic carbon storage community has raised further concerns because acidic fluids in the CO 2 storage reservoir, alkaline cement meant to isolate the reservoir fluids from the overlying strata, and steel casings in wells are inherently reactive systems. This is of particular concern for storage of CO 2 in depleted oil and gas reservoirs with numerous legacy wells engineered to variable standards. Research suggests that leakage risks are not as great as initially perceived because chemical and mechanical alteration of cement has the capacity to seal damaged zones. Our work centers on defining the coupled chemical and mechanical processes governing flow in damaged zones in wells. We have developed process-based models, constrained by experiments, to better understand and forecast leakage risk. Leakage pathways can be sealed by precipitation of carbonate minerals in the fractures and deformation of the reacted cement. High reactivity of cement hydroxides releases excess calcium that can precipitate as carbonate solids in the fracture network under low brine flow rates. If the flow is fast, then the brine remains undersaturated with respect to the solubility of calcium carbonate minerals, and zones depleted in calcium hydroxides, enriched in calcium carbonate precipitates, and made of amorphous silicates leached of original cement minerals are formed. Under confining pressure, the reacted cement is compressed, which reduces permeability and lowers leakage risks. The

Evaluating information in multiple horizon forecasts. The DOE's energy price forecasts

International Nuclear Information System (INIS)

Sanders, Dwight R.; Manfredo, Mark R.; Boris, Keith

2009-01-01

The United States Department of Energy's (DOE) quarterly price forecasts for energy commodities are examined to determine the incremental information provided at the one-through four-quarter forecast horizons. A direct test for determining information content at alternative forecast horizons, developed by Vuchelen and Gutierrez [Vuchelen, J. and Gutierrez, M.-I. 'A Direct Test of the Information Content of the OECD Growth Forecasts.' International Journal of Forecasting. 21(2005):103-117.], is used. The results suggest that the DOE's price forecasts for crude oil, gasoline, and diesel fuel do indeed provide incremental information out to three-quarters ahead, while natural gas and electricity forecasts are informative out to the four-quarter horizon. In contrast, the DOE's coal price forecasts at two-, three-, and four-quarters ahead provide no incremental information beyond that provided for the one-quarter horizon. Recommendations of how to use these results for making forecast adjustments is also provided. (author)

Behavior and dam passage of juvenile Chinook salmon at Cougar Reservoir and Dam, Oregon, March 2011 - February 2012

Science.gov (United States)

Beeman, John W.; Hansel, Hal C.; Hansen, Amy C.; Haner, Philip V.; Sprando, Jamie M.; Smith, Collin D.; Evans, Scott D.; Hatton, Tyson W.

2013-01-01

The movements and dam passage of juvenile Chinook salmon implanted with acoustic transmitters and passive integrated transponder tags were studied at Cougar Reservoir and Dam, near Springfield, Oregon. The purpose of the study was to provide information to aid with decisions about potential alternatives for improving downstream passage conditions for juvenile salmonids in this flood-control reservoir. In 2011, a total of 411 hatchery fish and 26 wild fish were tagged and released during a 3-month period in the spring, and another 356 hatchery fish and 117 wild fish were released during a 3-month period in the fall. A series of 16 autonomous hydrophones throughout the reservoir and 12 hydrophones in a collective system near the dam outlet were used to determine general movements and dam passage of the fish over the life of the acoustic transmitter, which was expected to be about 3 months. Movements within the reservoir were directional, and it was common for fish to migrate repeatedly from the head of the reservoir downstream to the dam outlet and back to the head of the reservoir. Most fish were detected near the temperature control tower at least once. The median time from release near the head of the reservoir to detection within about 100 meters of the dam outlet at the temperature control tower was between 5.7 and 10.8 days, depending on season and fish origin. Dam passage events occurred over a wider range of dates in the spring and summer than in the fall and winter, but dam passage numbers were greatest during the fall and winter. A total of 10.5 percent (43 of 411) of the hatchery fish and 15.4 percent (4 of 26) of the wild fish released in the spring are assumed to have passed the dam, whereas a total of 25.3 percent (90 of 356) of the hatchery fish and 16.9 percent (30 of 117) of the wild fish released in the fall are assumed to have passed the dam. A small number of fish passed the dam after their transmitters had stopped working and were detected at

[Effect of the Runoff-sediment Control of the Xiaolangdi Reservoir on DOC Transport].

Science.gov (United States)

Zhang, Yong-ling; Wang, Ming-shi; Dong, Yu-long

2015-04-01

The sampling was carried out in Sanmenxia hydrological station, Xiaolangdi hydrological station and Huayuankou hydrological station from November 2011 to October 2012. The impact of the runoff-sediment control of the Xiaolangdi reservoir on DOC transport,was analyzed. The results were as follows. DOC contents in Sanmenxia station, Xiaolangdi station and Huayuankou station were 1.97-2.71 mg-L(-1), 1.87-2.76 mg x L(-1) and 2.07-2.93 mg x L(-1), respectively, during the normal operation period of Xiaolangdi Reservoir and Sanmenxia reservoir, and the DOC content in the three reservoirs had obvious seasonal change. DOC contents in the three stations were 2.14-3.32 mg x L(-1), 2.21-2.84 mg x L(-1) and 2.11-2.84 mg x L(-1), respectively, during the runoff-sediment control, and the DOC content in the sediment-releasing period of reservoir was higher than that in the water-releasing period of reservoir. DOC content had no significant correlation with TSS and flow either during the normal operation or during the water-sediment regulation of the reservoir. But the DOC content had significant correlation with water temperature during the normal operation of the reservoir. DOC flux in Sanmenxia station was similar to that in Xiaolangdi station from November to March. DOC flux in Sanmenxia station was obviously less than that in Xiaolangdi station from April to July. And the DOC flux in Sanmenxia station was much higher than that in Xiaolangdi station from August to October. The result showed that DOC was retained from August to October by Xiaolangdi reservoir and discharged from Xiaolangdi reservoir from April to July. The yearly DOC fluxes were 8.6 x 10(10), 9.0 x 10(10) and 9.7 x 10(10) g respectively in Sanmenxia station, Xiaolangdi station and Huayuankou station. The DOC flux of Sanmenxia station was the highest in September, which accounted for 22.0% of the yearly DOC flux, and the DOC flux of Xiaolangdi station was the highest in June, which accounted for 17.6% of the

Survival Estimates for the Passage of Juvenile Salmonids through Snake River Dams and Reservoirs, 1994 Annual Report.

Energy Technology Data Exchange (ETDEWEB)

Muir, William D.

1995-02-01

In 1994, the National Marine Fisheries Service and the University of Washington completed the second year of a multi-year study to estimate survival of juvenile salmonids (Oncorhynchus spp.) passing through the dams and reservoirs of the Snake River. Actively migrating smolts were collected at selected locations above, at, and below Lower Granite Dam, tagged with passive integrated transponder (PIT) tags, and released to continue their downstream migration. Survival estimates were calculated using the Single-Release, Modified Single-Release, and Paired-Release Models.

Historical deposition and fluxes of mercury in Narraguinnep Reservoir, southwestern Colorado, USA

International Nuclear Information System (INIS)

Gray, John E.; Fey, David L.; Holmes, Charles W.; Lasorsa, Brenda K.

2005-01-01

Narraguinnep Reservoir has been identified as containing fish with elevated Hg concentrations and has been posted with an advisory recommending against consumption of fish. There are presently no point sources of significant Hg contamination to this reservoir or its supply waters. To evaluate potential historical Hg sources and deposition of Hg to Narraguinnep Reservoir, the authors measured Hg concentrations in sediment cores collected from this reservoir. The cores were dated by the 137 Cs method and these dates were further refined by relating water supply basin hydrological records with core sedimentology. Rates of historical Hg flux were calculated (ng/cm 2 /a) based on the Hg concentrations in the cores, sediment bulk densities, and sedimentation rates. The flux of Hg found in Narraguinnep Reservoir increased by approximately a factor of 2 after about 1970. The 3 most likely sources of Hg to Narraguinnep Reservoir are surrounding bedrocks, upstream inactive Au-Ag mines, and several coal-fired electric power plants in the Four Corners region. Patterns of Hg flux do not support dominant Hg derivation from surrounding bedrocks or upstream mining sources. There are 14 coal-fired power plants within 320 km of Narraguinnep Reservoir that produce over 80 x 10 6 MWH of power and about 1640 kg-Hg/a are released through stack emissions, contributing significant Hg to the surrounding environment. Two of the largest power plants, located within 80 km of the reservoir, emit about 950 kg-Hg/a. Spatial and temporal patterns of Hg fluxes for sediment cores collected from Narraguinnep Reservoir suggest that the most likely source of Hg to this reservoir is from atmospheric emissions from the coal-fired electric power plants, the largest of which began operation in this region in the late-1960s and early 1970s

Solar Particle Radiation Storms Forecasting and Analysis within the Framework of the `HESPERIA' HORIZON 2020 Project

Science.gov (United States)

Posner, A.; Malandraki, O.; Nunez, M.; Heber, B.; Labrenz, J.; Kühl, P.; Milas, N.; Tsiropoula, G.; Pavlos, E.

2017-12-01

Two prediction tools that have been developed in the framework of HESPERIA based upon the proven concepts UMASEP and REleASE. Near-relativistic (NR) electrons traveling faster than ions (30 MeV protons have 0.25c) are used to forecast the arrival of protons of Solar Energetic Particle (SEP) events with real-time measurements of NR electrons. The faster electrons arrive at L1 30 to 90 minutes before the slower protons. REleASE (Relativistic Electron Alert System for Exploration, Posner, 2007) uses this effect to predict the proton flux by utilizing actual electron fluxes and their most recent increases. Through HESPERIA, a clone of REleASE was built in open source programming language. The same forecasting principle was adapted to real-time data from ACE/EPAM. It is shown that HESPERIA REleASE forecasting works with any NR electron flux measurements. >500 MeV solar protons are so energetic that they usually have effects on the ground, producing Ground Level Enhancement (GLE) events. Within HESPERIA, a predictor of >500 SEP proton events near earth (geostationary orbit) has been developed. In order to predict these events, UMASEP (Núñez, 2011, 2015) has been used. UMASEP makes a lag-correlation of solar electromagnetic (EM) flux with the particle flux near earth. If the correlation is high, the model infers that there is a magnetic connection through which particles are arriving. If, additionally, the intensity of the flux of the associated solar event is also high, then UMASEP issues a SEP prediction. In the case of the prediction of >500 MeV SEP events, the implemented system, called HESPERIA UMASEP-500, correlates X-ray flux with differential proton fluxes by GOES, and with fluxes collected by neutron monitor stations around the world. When the correlation estimation and flare surpasses thresholds, a >500 MeV SEP forecast is issued. These findings suggest that a synthesis of the various approaches may improve over the status quo. Both forecasting tools are

National Forecast Charts

Science.gov (United States)

code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

Impacts of water quality variation and rainfall runoff on Jinpen Reservoir, in Northwest China

Directory of Open Access Journals (Sweden)

Zi-zhen Zhou

2015-10-01

Full Text Available The seasonal variation characteristics of the water quality of the Jinpen Reservoir and the impacts of rainfall runoff on the reservoir were investigated. Water quality monitoring results indicated that, during the stable stratification period, the maximum concentrations of total nitrogen, total phosphorus, ammonia nitrogen, total organic carbon, iron ion, and manganese ion in the water at the reservoir bottom on September 6 reached 2.5 mg/L, 0.12 mg/L, 0.58 mg/L, 3.2 mg/L, 0.97 mg/L, and 0.32 mg/L, respectively. Only heavy storm runoff can affect the main reservoir and cause the water quality to seriously deteriorate. During heavy storms, the stratification of the reservoir was destroyed, and the reservoir water quality consequently deteriorated due to the high-turbidity particulate phosphorus and organic matter in runoff. The turbidity and concentrations of total phosphorus and total organic carbon in the main reservoir increased to 265 NTU, 0.224 mg/L, and 3.9 mg/L, respectively. Potential methods of dealing with the water problems in the Jinpen Reservoir are proposed. Both in stratification and in storm periods, the use of measures such as adjusting intake height, storing clean water, and releasing turbid flow can be helpful to safeguarding the quality of water supplied to the water treatment plants.

Deep Learning Based Solar Flare Forecasting Model. I. Results for Line-of-sight Magnetograms

Science.gov (United States)

Huang, Xin; Wang, Huaning; Xu, Long; Liu, Jinfu; Li, Rong; Dai, Xinghua

2018-03-01

Solar flares originate from the release of the energy stored in the magnetic field of solar active regions, the triggering mechanism for these flares, however, remains unknown. For this reason, the conventional solar flare forecast is essentially based on the statistic relationship between solar flares and measures extracted from observational data. In the current work, the deep learning method is applied to set up the solar flare forecasting model, in which forecasting patterns can be learned from line-of-sight magnetograms of solar active regions. In order to obtain a large amount of observational data to train the forecasting model and test its performance, a data set is created from line-of-sight magnetogarms of active regions observed by SOHO/MDI and SDO/HMI from 1996 April to 2015 October and corresponding soft X-ray solar flares observed by GOES. The testing results of the forecasting model indicate that (1) the forecasting patterns can be automatically reached with the MDI data and they can also be applied to the HMI data; furthermore, these forecasting patterns are robust to the noise in the observational data; (2) the performance of the deep learning forecasting model is not sensitive to the given forecasting periods (6, 12, 24, or 48 hr); (3) the performance of the proposed forecasting model is comparable to that of the state-of-the-art flare forecasting models, even if the duration of the total magnetograms continuously spans 19.5 years. Case analyses demonstrate that the deep learning based solar flare forecasting model pays attention to areas with the magnetic polarity-inversion line or the strong magnetic field in magnetograms of active regions.

The use of various interplanetary scintillation indices within geomagnetic forecasts

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E. A. Lucek

Full Text Available Interplanetary scintillation (IPS, the twinkling of small angular diameter radio sources, is caused by the interaction of the signal with small-scale plasma irregularities in the solar wind. The technique may be used to sense remotely the near-Earth heliosphere and observations of a sufficiently large number of sources may be used to track large-scale disturbances as they propagate from close to the Sun to the Earth. Therefore, such observations have potential for use within geomagnetic forecasts. We use daily data from the Mullard Radio Astronomy Observatory, made available through the World Data Centre, to test the success of geomagnetic forecasts based on IPS observations. The approach discussed here was based on the reduction of the information in a map to a single number or series of numbers. The advantages of an index of this nature are that it may be produced routinely and that it could ideally forecast both the occurrence and intensity of geomagnetic activity. We start from an index that has already been described in the literature, INDEX35. On the basis of visual examination of the data in a full skymap format modifications were made to the way in which the index was calculated. It was hoped that these would lead to an improvement in its forecasting ability. Here we assess the forecasting potential of the index using the value of the correlation coefficient between daily Ap and the IPS index, with IPS leading by 1 day. We also compare the forecast based on the IPS index with forecasts of Ap currently released by the Space Environment Services Center (SESC. Although we find that the maximum improvement achieved is small, and does not represent a significant advance in forecasting ability, the IPS forecasts at this phase of the solar cycle are of a similar quality to those made by SESC.

Forecasting telecommunication new service demand by analogy method and combined forecast

Directory of Open Access Journals (Sweden)

Lin Feng-Jenq

2005-01-01

Full Text Available In the modeling forecast field, we are usually faced with the more difficult problems of forecasting market demand for a new service or product. A new service or product is defined as that there is absence of historical data in this new market. We hardly use models to execute the forecasting work directly. In the Taiwan telecommunication industry, after liberalization in 1996, there are many new services opened continually. For optimal investment, it is necessary that the operators, who have been granted the concessions and licenses, forecast this new service within their planning process. Though there are some methods to solve or avoid this predicament, in this paper, we will propose one forecasting procedure that integrates the concept of analogy method and the idea of combined forecast to generate new service forecast. In view of the above, the first half of this paper describes the procedure of analogy method and the approach of combined forecast, and the second half provides the case of forecasting low-tier phone demand in Taiwan to illustrate this procedure's feasibility.

Efficient Data Assimilation Tool For Real Time CO2 Reservoir Monitoring and Characterization

Science.gov (United States)

Li, J. Y.; Ambikasaran, S.; Kokkinaki, A.; Darve, E. F.; Kitanidis, P. K.

2014-12-01

Reservoir forecasting and management are increasingly relying on a data-driven approach, which involves data assimilation to calibrate and keep up to date the complex model of multi-phase flow and transport in the geologic formation and to evaluate its uncertainty using monitoring data of different types and temporal resolution. The numbers of unknowns and measurements are usually very large, which represents a major computational challenge. Kalman filter (KF), the archetypical recursive filter, provides the framework to assimilate reservoir monitoring data into a dynamic system but the cost of implementing the original algorithm to large systems is computationally prohibitive. In our work, we have developed several Kalman-filter based approaches that reduce the computational and storage cost of standard KF from O (m2) to O (m), where m is the number of unknowns, and have the potential to be applied to field-scale problems. HiKF, a linear filter based on the hierarchical matrix approach, takes advantage of the informative high-frequency data acquired quasi-continuously and uses a random-walk model in the state forecast step when the a state evolution model is unavailable. A more general-purpose nonlinear filter CSKF achieves computational efficiency by exploiting the fact that the state covariance matrix for most dynamical systems can be approximated adequately through a low-rank matrix, and it allows using a forward simulator as a black-box for nonlinear error propagation. We will demonstrate both methods using synthetic CO2 injection cases and compare with the standard ensemble Kalman filter (EnKF).

Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability

Science.gov (United States)

Papoulakos, Konstantinos; Pollakis, Giorgos; Moustakis, Yiannis; Markopoulos, Apostolis; Iliopoulou, Theano; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; Efstratiadis, Andreas

2017-04-01

Small islands are regarded as promising areas for developing hybrid water-energy systems that combine multiple sources of renewable energy with pumped-storage facilities. Essential element of such systems is the water storage component (reservoir), which implements both flow and energy regulations. Apparently, the representation of the overall water-energy management problem requires the simulation of the operation of the reservoir system, which in turn requires a faithful estimation of water inflows and demands of water and energy. Yet, in small-scale reservoir systems, this task in far from straightforward, since both the availability and accuracy of associated information is generally very poor. For, in contrast to large-scale reservoir systems, for which it is quite easy to find systematic and reliable hydrological data, in the case of small systems such data may be minor or even totally missing. The stochastic approach is the unique means to account for input data uncertainties within the combined water-energy management problem. Using as example the Livadi reservoir, which is the pumped storage component of the small Aegean island of Astypalaia, Greece, we provide a simulation framework, comprising: (a) a stochastic model for generating synthetic rainfall and temperature time series; (b) a stochastic rainfall-runoff model, whose parameters cannot be inferred through calibration and, thus, they are represented as correlated random variables; (c) a stochastic model for estimating water supply and irrigation demands, based on simulated temperature and soil moisture, and (d) a daily operation model of the reservoir system, providing stochastic forecasts of water and energy outflows. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students

Integrated Flood Forecast and Virtual Dam Operation System for Water Resources and Flood Risk Management

Science.gov (United States)

Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio

2014-05-01

While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.

Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

Energy Technology Data Exchange (ETDEWEB)

Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)

2006-11-01

The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensor packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging

Understanding and seasonal forecasting of hydrological drought in the Anthropocene

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X. Yuan

2017-11-01

Full Text Available Hydrological drought is not only caused by natural hydroclimate variability but can also be directly altered by human interventions including reservoir operation, irrigation, groundwater exploitation, etc. Understanding and forecasting of hydrological drought in the Anthropocene are grand challenges due to complicated interactions among climate, hydrology and humans. In this paper, five decades (1961–2010 of naturalized and observed streamflow datasets are used to investigate hydrological drought characteristics in a heavily managed river basin, the Yellow River basin in north China. Human interventions decrease the correlation between hydrological and meteorological droughts, and make the hydrological drought respond to longer timescales of meteorological drought. Due to large water consumptions in the middle and lower reaches, there are 118–262 % increases in the hydrological drought frequency, up to 8-fold increases in the drought severity, 21–99 % increases in the drought duration and the drought onset is earlier. The non-stationarity due to anthropogenic climate change and human water use basically decreases the correlation between meteorological and hydrological droughts and reduces the effect of human interventions on hydrological drought frequency while increasing the effect on drought duration and severity. A set of 29-year (1982–2010 hindcasts from an established seasonal hydrological forecasting system are used to assess the forecast skill of hydrological drought. In the naturalized condition, the climate-model-based approach outperforms the climatology method in predicting the 2001 severe hydrological drought event. Based on the 29-year hindcasts, the former method has a Brier skill score of 11–26 % against the latter for the probabilistic hydrological drought forecasting. In the Anthropocene, the skill for both approaches increases due to the dominant influence of human interventions that have been implicitly

Large reservoirs: Chapter 17

Science.gov (United States)

Miranda, Leandro E.; Bettoli, Phillip William

2010-01-01

Large impoundments, defined as those with surface area of 200 ha or greater, are relatively new aquatic ecosystems in the global landscape. They represent important economic and environmental resources that provide benefits such as flood control, hydropower generation, navigation, water supply, commercial and recreational fisheries, and various other recreational and esthetic values. Construction of large impoundments was initially driven by economic needs, and ecological consequences received little consideration. However, in recent decades environmental issues have come to the forefront. In the closing decades of the 20th century societal values began to shift, especially in the developed world. Society is no longer willing to accept environmental damage as an inevitable consequence of human development, and it is now recognized that continued environmental degradation is unsustainable. Consequently, construction of large reservoirs has virtually stopped in North America. Nevertheless, in other parts of the world construction of large reservoirs continues. The emergence of systematic reservoir management in the early 20th century was guided by concepts developed for natural lakes (Miranda 1996). However, we now recognize that reservoirs are different and that reservoirs are not independent aquatic systems inasmuch as they are connected to upstream rivers and streams, the downstream river, other reservoirs in the basin, and the watershed. Reservoir systems exhibit longitudinal patterns both within and among reservoirs. Reservoirs are typically arranged sequentially as elements of an interacting network, filter water collected throughout their watersheds, and form a mosaic of predictable patterns. Traditional approaches to fisheries management such as stocking, regulating harvest, and in-lake habitat management do not always produce desired effects in reservoirs. As a result, managers may expend resources with little benefit to either fish or fishing. Some locally

Understanding the True Stimulated Reservoir Volume in Shale Reservoirs

KAUST Repository

Hussain, Maaruf

2017-06-06

Successful exploitation of shale reservoirs largely depends on the effectiveness of hydraulic fracturing stimulation program. Favorable results have been attributed to intersection and reactivation of pre-existing fractures by hydraulically-induced fractures that connect the wellbore to a larger fracture surface area within the reservoir rock volume. Thus, accurate estimation of the stimulated reservoir volume (SRV) becomes critical for the reservoir performance simulation and production analysis. Micro-seismic events (MS) have been commonly used as a proxy to map out the SRV geometry, which could be erroneous because not all MS events are related to hydraulic fracture propagation. The case studies discussed here utilized a fully 3-D simulation approach to estimate the SRV. The simulation approach presented in this paper takes into account the real-time changes in the reservoir\\'s geomechanics as a function of fluid pressures. It is consisted of four separate coupled modules: geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive re-meshing. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Our simulations were run on a Cray XC-40 HPC system. The studies outcomes proved the approach of using MS data as a proxy for SRV to be significantly flawed. Many of the observed stimulated natural fractures are stress related and very few that are closer to the injection field are connected. The situation is worsened in a highly laminated shale reservoir as the hydraulic fracture propagation is significantly hampered. High contrast in the in-situ stresses related strike-slip developed thereby shortens the extent of SRV. However, far field nature fractures that were not connected to

New Technology Trends in Education: Seven Years of Forecasts and Convergence

Science.gov (United States)

Martin, Sergio; Diaz, Gabriel; Sancristobal, Elio; Gil, Rosario; Castro, Manuel; Peire, Juan

2011-01-01

Each year since 2004, a new Horizon Report has been released. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the mid-term (the next 2 years) and the long term (the next 4 years). This paper analyzes the evolution of technology trends…

FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting

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Miquel L. Alomar

2016-01-01

Full Text Available Hardware implementation of artificial neural networks (ANNs allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC has arisen as a strategic technique to design recurrent neural networks (RNNs with simple learning capabilities. In this work, we show a new approach to implement RC systems with digital gates. The proposed method is based on the use of probabilistic computing concepts to reduce the hardware required to implement different arithmetic operations. The result is the development of a highly functional system with low hardware resources. The presented methodology is applied to chaotic time-series forecasting.

Effect of reservoir heterogeneity on air injection performance in a light oil reservoir

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Hu Jia

2018-03-01

Full Text Available Air injection is a good option to development light oil reservoir. As well-known that, reservoir heterogeneity has great effect for various EOR processes. This also applies to air injection. However, oil recovery mechanisms and physical processes for air injection in heterogeneous reservoir with dip angle are still not well understood. The reported setting of reservoir heterogeneous for physical model or simulation model of air injection only simply uses different-layer permeability of porous media. In practice, reservoir heterogeneity follows the principle of geostatistics. How much of contrast in permeability actually challenges the air injection in light oil reservoir? This should be investigated by using layered porous medial settings of the classical Dykstra-Parsons style. Unfortunately, there has been no work addressing this issue for air injection in light oil reservoir. In this paper, Reservoir heterogeneity is quantified based on the use of different reservoir permeability distribution according to classical Dykstra-Parsons coefficients method. The aim of this work is to investigate the effect of reservoir heterogeneity on physical process and production performance of air injection in light oil reservoir through numerical reservoir simulation approach. The basic model is calibrated based on previous study. Total eleven pseudo compounders are included in this model and ten complexity of reactions are proposed to achieve the reaction scheme. Results show that oil recovery factor is decreased with the increasing of reservoir heterogeneity both for air and N2 injection from updip location, which is against the working behavior of air injection from updip location. Reservoir heterogeneity sometimes can act as positive effect to improve sweep efficiency as well as enhance production performance for air injection. High O2 content air injection can benefit oil recovery factor, also lead to early O2 breakthrough in heterogeneous reservoir. Well

Methane and CO2 emissions from China's hydroelectric reservoirs: a new quantitative synthesis.

Science.gov (United States)

Li, Siyue; Zhang, Quanfa; Bush, Richard T; Sullivan, Leigh A

2015-04-01

Controversy surrounds the green credentials of hydroelectricity because of the potentially large emission of greenhouse gases (GHG) from associated reservoirs. However, limited and patchy data particularly for China is constraining the current global assessment of GHG releases from hydroelectric reservoirs. This study provides the first evaluation of the CO2 and CH4 emissions from China's hydroelectric reservoirs by considering the reservoir water surface and drawdown areas, and downstream sources (including spillways and turbines, as well as river downstream). The total emission of 29.6 Tg CO2/year and 0.47 Tg CH4/year from hydroelectric reservoirs in China, expressed as CO2 equivalents (eq), corresponds to 45.6 Tg CO2eq/year, which is 2-fold higher than the current GHG emission (ca. 23 Tg CO2eq/year) from global temperate hydropower reservoirs. China's average emission of 70 g CO2eq/kWh from hydropower amounts to 7% of the emissions from coal-fired plant alternatives. China's hydroelectric reservoirs thus currently mitigate GHG emission when compared to the main alternative source of electricity with potentially far great reductions in GHG emissions and benefits possible through relatively minor changes to reservoir management and design. On average, the sum of drawdown and downstream emission including river reaches below dams and turbines, which is overlooked by most studies, represents the equivalent of 42% of the CO2 and 92% of CH4 that emit from hydroelectric reservoirs in China. Main drivers on GHG emission rates are summarized and highlight that water depth and stratification control CH4 flux, and CO2 flux shows significant negative relationships with pH, DO, and Chl-a. Based on our finding, a substantial revision of the global carbon emissions from hydroelectric reservoirs is warranted.

Carbon emission as a function of energy generation in hydroelectric reservoirs in Brazilian dry tropical biome

International Nuclear Information System (INIS)

Ometto, Jean P.; Cimbleris, André C.P.; Santos, Marco A. dos; Rosa, Luiz P.; Abe, Donato; Tundisi, José G.; Stech, José L.; Barros, Nathan; Roland, Fábio

2013-01-01

Most energy generation globally is fueled by coal and oil, raising concerns about greenhouse gas emissions. Hydroelectric reservoirs are anthropogenic aquatic systems that occur across a wide geographical extent, and, in addition to their importance for energy production, they have the potential to release two important greenhouse gases (GHGs), carbon dioxide and methane. We report results from an extensive study of eight hydroelectric reservoirs located in central and southeastern tropical Brazil. In the Brazilian dry tropical biome reservoirs, emissions (in tons of CO 2 Eq. per MW h) varied from 0.01 to 0.55, and decreased with reservoir age. Total emissions were higher in the reservoir lake when compared to the river downstream the dam; however, emissions per unit area, in the first kilometer of the river after the dam, were higher than that in the reservoir. The results showed, despite higher carbon emissions per energy production in the youngest reservoirs, lower emission from hydroelectric reservoirs from the studied region in relation to thermo electrical supply, fueled by coal or fossil fuel. The ratio emission of GHG per MWh produced is an important parameter in evaluating the service provided by hydroelectric reservoir and for energy planning policies. - Highlights: ► Hydroelectric reservoirs construction is growing worldwide. ► The effect of hydropower reservoir in the carbon cycle is dependent on environment characteristics. ► Carbon emissions per energy production are higher in the youngest tropical savannah reservoirs. ► Methane emissions decrease with reservoir age in tropical savannah reservoirs. ► In general, the effect of hydropower in the carbon cycle is lower than other energy sources

Ensemble-based simultaneous emission estimates and improved forecast of radioactive pollution from nuclear power plant accidents: application to ETEX tracer experiment

International Nuclear Information System (INIS)

Zhang, X.L.; Li, Q.B.; Su, G.F.; Yuan, M.Q.

2015-01-01

The accidental release of radioactive materials from nuclear power plant leads to radioactive pollution. We apply an augmented ensemble Kalman filter (EnKF) with a chemical transport model to jointly estimate the emissions of Perfluoromethylcyclohexane (PMCH), a tracer substitute for radionuclides, from a point source during the European Tracer Experiment, and to improve the forecast of its dispersion downwind. We perturb wind fields to account for meteorological uncertainties. We expand the state vector of PMCH concentrations through continuously adding an a priori emission rate for each succeeding assimilation cycle. We adopt a time-correlated red noise to simulate the temporal emission fluctuation. The improved EnKF system rapidly updates (and reduces) the excessively large initial first-guess emissions, thereby significantly improves subsequent forecasts (r = 0.83, p < 0.001). It retrieves 94% of the total PMCH released and substantially reduces transport error (>80% average reduction of the normalized mean square error). - Highlights: • EnKF is augmented for estimating emission and improving dispersion forecast. • The improved system retrieves 94% of the actual total tracer release in ETEX. • The system substantially improves the 3-h forecast of the tracer dispersion. • The method is robust and insensitive to the first-guess emissions. • The meteorological uncertainties exert strong influence on the performance

Inflation Forecast Contracts

OpenAIRE

Gersbach, Hans; Hahn, Volker

2012-01-01

We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

Corps Water Management System (CWMS) Decision Support Modeling and Integration Use in the June 2007 Texas Floods

Science.gov (United States)

Charley, W. J.; Luna, M.

2007-12-01

The U.S. Army Corps of Engineers Corps Water Management System (CWMS) is a comprehensive data acquisition and hydrologic modeling system for short-term decision support of water control operations in real time. It encompasses data collection, validation and transformation, data storage, visualization, real time model simulation for decision-making support, and data dissemination. CWMS uses an Oracle database and Sun Solaris workstations for data processes, storage and the execution of models, with a client application (the Control and Visualization Interface, or CAVI) that can run on a Windows PC. CWMS was used by the Lower Colorado River Authority (LCRA) to make hydrologic forecasts of flows on the Lower Colorado River and operate reservoirs during the June 2007 event in Texas. The LCRA receives real-time observed gridded spatial rainfall data from OneRain, Inc. that which is a result of adjusting NexRad rainfall data with precipitation gages. This data is used, along with future precipitation estimates, for hydrologic forecasting by the rainfall-runoff modeling program HEC-HMS. Forecasted flows from HEC-HMS and combined with observed flows and reservoir information to simulate LCRA's reservoir operations and help engineers make release decisions based on the results. The river hydraulics program, HEC-RAS, computes river stages and water surface profiles for the computed flow. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. By varying future precipitation and releases, engineers can evaluate different "What if?" scenarios. What was described as an "extraordinary cluster of thunderstorms" that stalled over Burnet and Llano counties in Texas on June 27, 2007, dropped 17 to 19 inches of rainfall over a 6-hour period. The storm was classified over a 500-year event and the resulting flow over some of the smaller tributaries as a 100-year or better. CWMS was used by LCRA for flood forecasting and

EOS simulation and GRNN modeling of the constant volume depletion behavior of gas condensate reservoirs

Energy Technology Data Exchange (ETDEWEB)

Elsharkawy, A.M.; Foda, S.G. [Kuwait University, Safat (Kuwait). Petroleum Engineering Dept.

1998-03-01

Currently, two approaches are being used to predict the changes in retrograde gas condensate composition and estimate the pressure depletion behavior of gas condensate reservoirs. The first approach uses the equation of states whereas the second uses empirical correlations. Equations of states (EOS) are poor predictive tools for complex hydrocarbon systems. The EOS needs adjustment against phase behavior data of reservoir fluid of known composition. The empirical correlation does not involve numerous numerical computations but their accuracy is limited. This study presents two general regression neural network (GRNN) models. The first model, GRNNM1, is developed to predict dew point pressure and gas compressibility at dew point using initial composition of numerous samples while the second model, GRNNM2, is developed to predict the changes in well stream effluent composition at any stages of pressure depletion. GRNNM2 can also be used to determine the initial reservoir fluid composition using dew point pressure, gas compressibility at dew point, and reservoir temperature. These models are based on analysis of 142 sample of laboratory studies of constant volume depletion (CVD) for gas condensate systems forming a total of 1082 depletion stages. The database represents a wide range of gas condensate systems obtained worldwide. The performance of the GRNN models has been compared to simulation results of the equation of state. The study shows that the proposed general regression neural network models are accurate, valid, and reliable. These models can be used to forecast CVD data needed for many reservoir engineering calculations in case laboratory data is unavailable. The GRNN models save computer time involved in EOS calculations. The study also show that once these models are properly trained they can be used to cut expenses of frequent sampling and laborious experimental CVD tests required for gas condensate reservoirs. 55 refs., 13 figs., 6 tabs.

Release of volatile compounds from polymeric microcapsules mediated by photocatalytic nanoparticles

OpenAIRE

Marques, Juliana Filipa Gouveia; Oiveira, L. Filipa; Pinto, Renato; Coutinho, Paulo J. G.; Parpot, Pier; Gois, J. R.; Coelho, J. F. J.; Magalhães, F. D.; Tavares, C. J.

2013-01-01

In this study we propose a suitable method for the solar-activated controlled release of volatile compounds from polymeric microcapsules bonded with photocatalytic nanoparticles. These reservoirs can find applications, for example, in the controlled release of insecticides, repellents, or fragrances, amongst other substances. The surfaces of the microcapsules have been functionalized with TiO2 nanoparticles.Upon ultraviolet irradiation, redox mechanisms are initiated on the semicondu...

Channel-Mediated Lactate Release by K+-Stimulated Astrocytes

KAUST Repository

Sotelo-Hitschfeld, T.

2015-03-11

Excitatory synaptic transmission is accompanied by a local surge in interstitial lactate that occurs despite adequate oxygen availability, a puzzling phenomenon termed aerobic glycolysis. In addition to its role as an energy substrate, recent studies have shown that lactate modulates neuronal excitability acting through various targets, including NMDA receptors and G-protein-coupled receptors specific for lactate, but little is known about the cellular and molecular mechanisms responsible for the increase in interstitial lactate. Using a panel of genetically encoded fluorescence nanosensors for energy metabolites, we show here that mouse astrocytes in culture, in cortical slices, and in vivo maintain a steady-state reservoir of lactate. The reservoir was released to the extracellular space immediately after exposure of astrocytes to a physiological rise in extracellular K+ or cell depolarization. Cell-attached patch-clamp analysis of cultured astrocytes revealed a 37 pS lactate-permeable ion channel activated by cell depolarization. The channel was modulated by lactate itself, resulting in a positive feedback loop for lactate release. A rapid fall in intracellular lactate levels was also observed in cortical astrocytes of anesthetized mice in response to local field stimulation. The existence of an astrocytic lactate reservoir and its quick mobilization via an ion channel in response to a neuronal cue provides fresh support to lactate roles in neuronal fueling and in gliotransmission.

Operational Precipitation prediction in Support of Real-Time Flash Flood Prediction and Reservoir Management

Science.gov (United States)

Georgakakos, K. P.

2006-05-01

The presentation will outline the implementation and performance evaluation of a number of national and international projects pertaining to operational precipitation estimation and prediction in the context of hydrologic warning systems and reservoir management support. In all cases, uncertainty measures of the estimates and predictions are an integral part of the precipitation models. Outstanding research issues whose resolution is likely to lead to improvements in the operational environment are presented. The presentation draws from the experience of the Hydrologic Research Center (http://www.hrc-lab.org) prototype implementation projects at the Panama Canal, Central America, Northern California, and South-Central US. References: Carpenter, T.M, and K.P. Georgakakos, "Discretization Scale Dependencies of the Ensemble Flow Range versus Catchment Area Relationship in Distributed Hydrologic Modeling," Journal of Hydrology, 2006, in press. Carpenter, T.M., and K.P. Georgakakos, "Impacts of Parametric and Radar Rainfall Uncertainty on the Ensemble Streamflow Simulations of a Distributed Hydrologic Model," Journal of Hydrology, 298, 202-221, 2004. Georgakakos, K.P., Graham, N.E., Carpenter, T.M., Georgakakos, A.P., and H. Yao, "Integrating Climate- Hydrology Forecasts and Multi-Objective Reservoir Management in Northern California," EOS, 86(12), 122,127, 2005. Georgakakos, K.P., and J.A. Sperfslage, "Operational Rainfall and Flow Forecasting for the Panama Canal Watershed," in The Rio Chagres: A Multidisciplinary Profile of a Tropical Watershed, R.S. Harmon, ed., Kluwer Academic Publishers, The Netherlands, Chapter 16, 323-334, 2005. Georgakakos, K. P., "Analytical results for operational flash flood guidance," Journal of Hydrology, doi:10.1016/j.jhydrol.2005.05.009, 2005.

Amplitude various angles (AVA) phenomena in thin layer reservoir: Case study of various reservoirs

Energy Technology Data Exchange (ETDEWEB)

Nurhandoko, Bagus Endar B., E-mail: bagusnur@bdg.centrin.net.id, E-mail: bagusnur@rock-fluid.com [Wave Inversion and Subsurface Fluid Imaging Research Laboratory (WISFIR), Basic Science Center A 4" t" hfloor, Physics Dept., FMIPA, Institut Teknologi Bandung (Indonesia); Rock Fluid Imaging Lab., Bandung (Indonesia); Susilowati, E-mail: bagusnur@bdg.centrin.net.id, E-mail: bagusnur@rock-fluid.com [Rock Fluid Imaging Lab., Bandung (Indonesia)

2015-04-16

Amplitude various offset is widely used in petroleum exploration as well as in petroleum development field. Generally, phenomenon of amplitude in various angles assumes reservoir’s layer is quite thick. It also means that the wave is assumed as a very high frequency. But, in natural condition, the seismic wave is band limited and has quite low frequency. Therefore, topic about amplitude various angles in thin layer reservoir as well as low frequency assumption is important to be considered. Thin layer reservoir means the thickness of reservoir is about or less than quarter of wavelength. In this paper, I studied about the reflection phenomena in elastic wave which considering interference from thin layer reservoir and transmission wave. I applied Zoeppritz equation for modeling reflected wave of top reservoir, reflected wave of bottom reservoir, and also transmission elastic wave of reservoir. Results show that the phenomena of AVA in thin layer reservoir are frequency dependent. Thin layer reservoir causes interference between reflected wave of top reservoir and reflected wave of bottom reservoir. These phenomena are frequently neglected, however, in real practices. Even though, the impact of inattention in interference phenomena caused by thin layer in AVA may cause inaccurate reservoir characterization. The relation between classes of AVA reservoir and reservoir’s character are different when effect of ones in thin reservoir and ones in thick reservoir are compared. In this paper, I present some AVA phenomena including its cross plot in various thin reservoir types based on some rock physics data of Indonesia.

Amplitude various angles (AVA) phenomena in thin layer reservoir: Case study of various reservoirs

International Nuclear Information System (INIS)

thfloor, Physics Dept., FMIPA, Institut Teknologi Bandung (Indonesia); Rock Fluid Imaging Lab., Bandung (Indonesia))" data-affiliation=" (Wave Inversion and Subsurface Fluid Imaging Research Laboratory (WISFIR), Basic Science Center A 4thfloor, Physics Dept., FMIPA, Institut Teknologi Bandung (Indonesia); Rock Fluid Imaging Lab., Bandung (Indonesia))" >Nurhandoko, Bagus Endar B.; Susilowati

2015-01-01

Amplitude various offset is widely used in petroleum exploration as well as in petroleum development field. Generally, phenomenon of amplitude in various angles assumes reservoir’s layer is quite thick. It also means that the wave is assumed as a very high frequency. But, in natural condition, the seismic wave is band limited and has quite low frequency. Therefore, topic about amplitude various angles in thin layer reservoir as well as low frequency assumption is important to be considered. Thin layer reservoir means the thickness of reservoir is about or less than quarter of wavelength. In this paper, I studied about the reflection phenomena in elastic wave which considering interference from thin layer reservoir and transmission wave. I applied Zoeppritz equation for modeling reflected wave of top reservoir, reflected wave of bottom reservoir, and also transmission elastic wave of reservoir. Results show that the phenomena of AVA in thin layer reservoir are frequency dependent. Thin layer reservoir causes interference between reflected wave of top reservoir and reflected wave of bottom reservoir. These phenomena are frequently neglected, however, in real practices. Even though, the impact of inattention in interference phenomena caused by thin layer in AVA may cause inaccurate reservoir characterization. The relation between classes of AVA reservoir and reservoir’s character are different when effect of ones in thin reservoir and ones in thick reservoir are compared. In this paper, I present some AVA phenomena including its cross plot in various thin reservoir types based on some rock physics data of Indonesia

A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Chengshi Tian

2018-03-01

Full Text Available Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is successfully developed in this system, which further improves the effectiveness of data pre-processing and then enhances the final forecasting performance. Furthermore, the modified support vector machine is developed to integrate all the individual predictors and obtain the final prediction, which successfully overcomes the upper drawbacks of the linear combined model. Moreover, the evaluation module is incorporated to perform a scientific evaluation for the developed system. The half-hourly electrical load data from New South Wales are employed to verify the effectiveness of the developed forecasting system, and the results reveal that the developed nonlinear forecasting system can be employed in the dispatching and planning for smart grids.

GIS model-based real-time hydrological forecasting and operation management system for the Lake Balaton and its watershed

Science.gov (United States)

Adolf Szabó, János; Zoltán Réti, Gábor; Tóth, Tünde

2017-04-01

Today, the most significant mission of the decision makers on integrated water management issues is to carry out sustainable management for sharing the resources between a variety of users and the environment under conditions of considerable uncertainty (such as climate/land-use/population/etc. change) conditions. In light of this increasing water management complexity, we consider that the most pressing needs is to develop and implement up-to-date GIS model-based real-time hydrological forecasting and operation management systems for aiding decision-making processes to improve water management. After years of researches and developments the HYDROInform Ltd. has developed an integrated, on-line IT system (DIWA-HFMS: DIstributed WAtershed - Hydrologyc Forecasting & Modelling System) which is able to support a wide-ranging of the operational tasks in water resources management such as: forecasting, operation of lakes and reservoirs, water-control and management, etc. Following a test period, the DIWA-HFMS has been implemented for the Lake Balaton and its watershed (in 500 m resolution) at Central-Transdanubian Water Directorate (KDTVIZIG). The significant pillars of the system are: - The DIWA (DIstributed WAtershed) hydrologic model, which is a 3D dynamic water-balance model that distributed both in space and its parameters, and which was developed along combined principles but its mostly based on physical foundations. The DIWA integrates 3D soil-, 2D surface-, and 1D channel-hydraulic components as well. - Lakes and reservoir-operating component; - Radar-data integration module; - fully online data collection tools; - scenario manager tool to create alternative scenarios, - interactive, intuitive, highly graphical user interface. In Vienna, the main functions, operations and results-management of the system will be presented.

Medium Range Forecasts Representation (and Long Range Forecasts?)

Science.gov (United States)

Vincendon, J.-C.

2009-09-01

The progress of the numerical forecasts urges us to interest us in more and more distant ranges. We thus supply more and more forecasts with term of some days. Nevertheless, precautions of use are necessary to give the most reliable and the most relevant possible information. Available in a TV bulletin or on quite other support (Internet, mobile phone), the interpretation and the representation of a medium range forecast (5 - 15 days) must be different from those of a short range forecast. Indeed, the "foresee-ability” of a meteorological phenomenon decreases gradually in the course of the ranges, it decreases all the more quickly that the phenomenon is of small scale. So, at the end of some days, the probability character of a forecast becomes very widely dominating. That is why in Meteo-France the forecasts of D+4 to D+7 are accompanied with a confidence index since around ten years. It is a figure between 1 and 5: the more we approach 5, the more the confidence in the supplied forecast is good. In the practice, an indication is supplied for period D+4 / D+5, the other one for period D+6 / D+7, every day being able to benefit from a different forecast, that is be represented in a independent way. We thus supply a global tendency over 24 hours with less and less precise symbols as the range goes away. Concrete examples will be presented. From now on two years, we also publish forecasts to D+8 / J+9, accompanied with a sign of confidence (" good reliability " or " to confirm "). These two days are grouped together on a single map because for us, the described tendency to this term is relevant on a duration about 48 hours with a spatial scale slightly superior to the synoptic scale. So, we avoid producing more than two zones of types of weather over France and we content with giving an evolution for the temperatures (still, in increase or in decline). Newspapers began to publish this information, it should soon be the case of televisions. It is particularly

Study of Mg-based materials to be used in a functional solid state hydrogen reservoir for vehicular applications

Energy Technology Data Exchange (ETDEWEB)

Maddalena, Amedeo; Petris, Milo; Palade, Petru; Sartori, Sabrina; Principi, Giovanni [Settore Materiali and CNISM, Dipartimento di Ingegneria Meccanica, Universita di Padova, via Marzolo 9, 35131 Padova (Italy); Settimo, Eliseo [Celco-Profil, via dell' Artigianato 4, 30030 Vigonovo (Venezia) (Italy); Molinas, Bernardo [Venezia Tecnologie, via delle Industrie 39, 30175 Marghera (Venezia) (Italy); Lo Russo, Sergio [Dipartimento di Fisica and CNISM, Universita di Padova, via Marzolo 8, 35131 Padova (Italy)

2006-11-15

Powders mixtures of nanosized MgH{sub 2} and suitable additives, obtained by high energy milling, have been studied as materials to be used in a functional solid state hydrogen reservoir. A prototype of a two stages reservoir is under development (patent pending). The hydrogen release from the main stage, with high capacity Mg-based hydrides, is primed by a primer stage containing commercial hydrides able to operate at room temperature. (author)

Arsenic release from arsenopyrite weathering: Insights from sequential extraction and microscopic studies

Energy Technology Data Exchange (ETDEWEB)

Basu, Ankan [Marshall Miller and Associates, Bluefield VA (United States); Department of Geosciences, Virginia Tech, 4044 Derring Hall, Blacksburg VA 24061 (United States); Schreiber, Madeline E., E-mail: mschreib@vt.edu [Department of Geosciences, Virginia Tech, 4044 Derring Hall, Blacksburg VA 24061 (United States)

2013-11-15

Highlights: ► We studied arsenopyrite weathering reactions in rocks and sediments at mine site. ► Arsenopyrite oxidizes to scorodite, which dissolves incongruently to Fe hydroxide. ► Weathering of arsenopyrite to Fe hydroxide releases As to water. ► Dominant As reservoir in sediment is Fe hydroxide. -- Abstract: At a former As mine site, arsenopyrite oxidation has resulted in formation of scorodite and As-bearing iron hydroxide, both in host rock and mine tailings. Electron microprobe analysis documents that arsenopyrite weathers along two pathways: one that involves formation of sulfur, and one that does not. In both pathways, arsenopyrite oxidizes to form scorodite, which dissolves incongruently to form As-bearing iron hydroxides. From a mass balance perspective, arsenopyrite oxidation to scorodite conserves As, but as scorodite dissolves incongruently to iron hydroxides, As is released to solution, resulting in elevated As concentrations in the headwater stream adjacent to the site. The As-bearing iron hydroxide is the dominant solid phase reservoir of As in mine tailings and stream sediment, as suggested by sequential extraction. This As-bearing iron hydroxide is stable under the aerobic and pH 4–6 conditions at the site; however, changes in biogeochemical conditions resulting from sediment burial or future remedial efforts, which could promote As release from this reservoir due to reductive dissolution, should be avoided.

Arsenic release from arsenopyrite weathering: Insights from sequential extraction and microscopic studies

International Nuclear Information System (INIS)

Basu, Ankan; Schreiber, Madeline E.

2013-01-01

Highlights: ► We studied arsenopyrite weathering reactions in rocks and sediments at mine site. ► Arsenopyrite oxidizes to scorodite, which dissolves incongruently to Fe hydroxide. ► Weathering of arsenopyrite to Fe hydroxide releases As to water. ► Dominant As reservoir in sediment is Fe hydroxide. -- Abstract: At a former As mine site, arsenopyrite oxidation has resulted in formation of scorodite and As-bearing iron hydroxide, both in host rock and mine tailings. Electron microprobe analysis documents that arsenopyrite weathers along two pathways: one that involves formation of sulfur, and one that does not. In both pathways, arsenopyrite oxidizes to form scorodite, which dissolves incongruently to form As-bearing iron hydroxides. From a mass balance perspective, arsenopyrite oxidation to scorodite conserves As, but as scorodite dissolves incongruently to iron hydroxides, As is released to solution, resulting in elevated As concentrations in the headwater stream adjacent to the site. The As-bearing iron hydroxide is the dominant solid phase reservoir of As in mine tailings and stream sediment, as suggested by sequential extraction. This As-bearing iron hydroxide is stable under the aerobic and pH 4–6 conditions at the site; however, changes in biogeochemical conditions resulting from sediment burial or future remedial efforts, which could promote As release from this reservoir due to reductive dissolution, should be avoided

Earthquake focal mechanism forecasting in Italy for PSHA purposes

Science.gov (United States)

Roselli, Pamela; Marzocchi, Warner; Mariucci, Maria Teresa; Montone, Paola

2018-01-01

In this paper, we put forward a procedure that aims to forecast focal mechanism of future earthquakes. One of the primary uses of such forecasts is in probabilistic seismic hazard analysis (PSHA); in fact, aiming at reducing the epistemic uncertainty, most of the newer ground motion prediction equations consider, besides the seismicity rates, the forecast of the focal mechanism of the next large earthquakes as input data. The data set used to this purpose is relative to focal mechanisms taken from the latest stress map release for Italy containing 392 well-constrained solutions of events, from 1908 to 2015, with Mw ≥ 4 and depths from 0 down to 40 km. The data set considers polarity focal mechanism solutions until to 1975 (23 events), whereas for 1976-2015, it takes into account only the Centroid Moment Tensor (CMT)-like earthquake focal solutions for data homogeneity. The forecasting model is rooted in the Total Weighted Moment Tensor concept that weighs information of past focal mechanisms evenly distributed in space, according to their distance from the spatial cells and magnitude. Specifically, for each cell of a regular 0.1° × 0.1° spatial grid, the model estimates the probability to observe a normal, reverse, or strike-slip fault plane solution for the next large earthquakes, the expected moment tensor and the related maximum horizontal stress orientation. These results will be available for the new PSHA model for Italy under development. Finally, to evaluate the reliability of the forecasts, we test them with an independent data set that consists of some of the strongest earthquakes with Mw ≥ 3.9 occurred during 2016 in different Italian tectonic provinces.

INNOVATIVE MIOR PROCESS UTILIZING INDIGENOUS RESERVOIR CONSTITUENTS

Energy Technology Data Exchange (ETDEWEB)

D.O. Hitzman; S.A. Bailey

2000-01-01

This research program is directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal is to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery.This microbial technology has the capability of producing multiple oil releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery. Research has begun on the program and experimental laboratory work is underway. Polymer-producing cultures have been isolated from produced water samples and initially characterized. Concurrently, a microcosm scale sand-packed column has been designed and developed for testing cultures of interest, including polymer-producing strains. In research that is planned to begin in future work, comparative laboratory studies demonstrating in situ production of microbial products as oil recovery agents will be conducted in sand pack and cores with synthetic and natural field waters at concentrations, flooding rates, and with cultures and conditions representative of oil reservoirs.

The strategy of professional forecasting

DEFF Research Database (Denmark)

Ottaviani, Marco; Sørensen, Peter Norman

2006-01-01

We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

Identifying needs for streamflow forecasting in the Incomati basin, Southern Africa

Science.gov (United States)

Sunday, Robert; Werner, Micha; Masih, Ilyas; van der Zaag, Pieter

2013-04-01

little detail and clarity. In some cases this was attributed to the short time and space allotted in media such as television and newspapers respectively. Major uses of the weather forecast were made in personal planning i.e., travelling (29%) and dressing (23%). The usefulness in water sector was reported for water allocation (23%), farming (11%) and flood monitoring (9%), but was considered as a factor having minor influence on the actual decision making in operational water management mainly due to uncertainty of the weather forecast, difference in the time scale and institutional arrangements. In the incidences where streamflow forecasts were received (5% of the cases), its application in decision making was not carried out due to high uncertainty. Moreover, dam operators indicated weekly streamflow forecast as very important in releasing water for agriculture but this was not the format in which forecasts were available to them. Generally, users affirmed the accuracy and benefits of weather forecasts and had no major concerns on the impacts of wrong forecasts. However, respondents indicated the need to improve the accuracy and accessibility of the forecast. Likewise, water managers expressed the need for both rainfall and flow forecasts but indicated that they face hindrances due to financial and human resource constraints. This shows that there is a need to strengthen water related forecasts and the consequent uses in the basin. This can be done through collaboration among forecasting and water organisations such as the SAWS, Research Institutions and users like ICMA, KOBWA and farmers. Collaboration between the meteorology and water resources sectors is important to establish consistent forecast information. The forecasts themselves should be detailed and user specific to ensure these are indeed used and can answer to the needs of the users.

Evaluating changes to reservoir rule curves using historical water-level data

Science.gov (United States)

Mower, Ethan; Miranda, Leandro E.

2013-01-01

Flood control reservoirs are typically managed through rule curves (i.e. target water levels) which control the storage and release timing of flood waters. Changes to rule curves are often contemplated and requested by various user groups and management agencies with no information available about the actual flood risk of such requests. Methods of estimating flood risk in reservoirs are not easily available to those unfamiliar with hydrological models that track water movement through a river basin. We developed a quantile regression model that uses readily available daily water-level data to estimate risk of spilling. Our model provided a relatively simple process for estimating the maximum applicable water level under a specific flood risk for any day of the year. This water level represents an upper-limit umbrella under which water levels can be operated in a variety of ways. Our model allows the visualization of water-level management under a user-specified flood risk and provides a framework for incorporating the effect of a changing environment on water-level management in reservoirs, but is not designed to replace existing hydrological models. The model can improve communication and collaboration among agencies responsible for managing natural resources dependent on reservoir water levels.

Assessing ecosystem effects of reservoir operations using food web-energy transfer and water quality models

Science.gov (United States)

Saito, L.; Johnson, B.M.; Bartholow, J.; Hanna, R.B.

2001-01-01

We investigated the effects on the reservoir food web of a new temperature control device (TCD) on the dam at Shasta Lake, California. We followed a linked modeling approach that used a specialized reservoir water quality model to forecast operation-induced changes in phytoplankton production. A food web–energy transfer model was also applied to propagate predicted changes in phytoplankton up through the food web to the predators and sport fishes of interest. The food web–energy transfer model employed a 10% trophic transfer efficiency through a food web that was mapped using carbon and nitrogen stable isotope analysis. Stable isotope analysis provided an efficient and comprehensive means of estimating the structure of the reservoir's food web with minimal sampling and background data. We used an optimization procedure to estimate the diet proportions of all food web components simultaneously from their isotopic signatures. Some consumers were estimated to be much more sensitive than others to perturbations to phytoplankton supply. The linked modeling approach demonstrated that interdisciplinary efforts enhance the value of information obtained from studies of managed ecosystems. The approach exploited the strengths of engineering and ecological modeling methods to address concerns that neither of the models could have addressed alone: (a) the water quality model could not have addressed quantitatively the possible impacts to fish, and (b) the food web model could not have examined how phytoplankton availability might change due to reservoir operations.

Are Forecast Updates Progressive?

NARCIS (Netherlands)

C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

2010-01-01

textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

Cascade reservoir flood control operation based on risk grading and warning in the Upper Yellow River

Science.gov (United States)

Xuejiao, M.; Chang, J.; Wang, Y.

2017-12-01

Flood risk reduction with non-engineering measures has become the main idea for flood management. It is more effective for flood risk management to take various non-engineering measures. In this paper, a flood control operation model for cascade reservoirs in the Upper Yellow River was proposed to lower the flood risk of the water system with multi-reservoir by combining the reservoir flood control operation (RFCO) and flood early warning together. Specifically, a discharge control chart was employed to build the joint RFCO simulation model for cascade reservoirs in the Upper Yellow River. And entropy-weighted fuzzy comprehensive evaluation method was adopted to establish a multi-factorial risk assessment model for flood warning grade. Furthermore, after determining the implementing mode of countermeasures with future inflow, an intelligent optimization algorithm was used to solve the optimization model for applicable water release scheme. In addition, another model without any countermeasure was set to be a comparative experiment. The results show that the model developed in this paper can further decrease the flood risk of water system with cascade reservoirs. It provides a new approach to flood risk management by coupling flood control operation and flood early warning of cascade reservoirs.

Environmental factors that influence cyanobacteria and geosmin occurrence in reservoirs

Science.gov (United States)

Journey, Celeste A.; Beaulieu, Karen M.; Bradley, Paul M.; Bradley, Paul M.

2013-01-01

Phytoplankton are small to microscopic, free-floating algae that inhabit the open water of freshwater, estuarine, and saltwater systems. In freshwater lake and reservoirs systems, which are the focus of this chapter, phytoplankton communities commonly consist of assemblages of the major taxonomic groups, including green algae, diatoms, dinoflagellates, and cyanobacteria. Cyanobacteria are a diverse group of single-celled organisms that can exist in a wide range of environments, not just open water, because of their adaptability. It is the adaptability of cyanobacteria that enables this group to dominate the phytoplankton community and even form nuisance or harmful blooms under certain environmental conditions. In fact, cyanobacteria are predicted to adapt favorably to future climate change in freshwater systems compared to other phytoplankton groups because of their tolerance to rising temperatures, enhanced vertical thermal stratification of aquatic ecosystems, and alterations in seasonal and interannual weather patterns. Understanding those environmental conditions that favor cyanobacterial dominance and bloom formation has been the focus of research throughout the world because of the concomitant production and release of nuisance and toxic cyanobacterial-derived compounds. However, the complex interaction among the physical, chemical, and biological processes within lakes, reservoirs, and large rivers often makes it difficult to identify primary environmental factors that cause the production and release of these cyanobacterial by-products.

Optimal and centralized reservoir management for drought and flood protection via Stochastic Dual Dynamic Programming on the Upper Seine-Aube River system

Science.gov (United States)

Chiavico, Mattia; Raso, Luciano; Dorchies, David; Malaterre, Pierre-Olivier

2015-04-01

Seine river region is an extremely important logistic and economic junction for France and Europe. The hydraulic protection of most part of the region relies on four controlled reservoirs, managed by EPTB Seine-Grands Lacs. Presently, reservoirs operation is not centrally coordinated, and release rules are based on empirical filling curves. In this study, we analyze how a centralized release policy can face flood and drought risks, optimizing water system efficiency. The optimal and centralized decisional problem is solved by Stochastic Dual Dynamic Programming (SDDP) method, minimizing an operational indicator for each planning objective. SDDP allows us to include into the system: 1) the hydrological discharge, specifically a stochastic semi-distributed auto-regressive model, 2) the hydraulic transfer model, represented by a linear lag and route model, and 3) reservoirs and diversions. The novelty of this study lies on the combination of reservoir and hydraulic models in SDDP for flood and drought protection problems. The study case covers the Seine basin until the confluence with Aube River: this system includes two reservoirs, the city of Troyes, and the Nuclear power plant of Nogent-Sur-Seine. The conflict between the interests of flood protection, drought protection, water use and ecology leads to analyze the environmental system in a Multi-Objective perspective.

Load forecasting

International Nuclear Information System (INIS)

Mak, H.

1995-01-01

Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

Relating Tropical Cyclone Track Forecast Error Distributions with Measurements of Forecast Uncertainty

Science.gov (United States)

2016-03-01

CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS WITH MEASUREMENTS OF FORECAST UNCERTAINTY by Nicholas M. Chisler March 2016 Thesis Advisor...March 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE RELATING TROPICAL CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS...WITH MEASUREMENTS OF FORECAST UNCERTAINTY 5. FUNDING NUMBERS 6. AUTHOR(S) Nicholas M. Chisler 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES

Forecasting of reservoir pressures of oil and gas bearing complexes in northern part of West Siberia for safety oil and gas deposits exploration and development

Science.gov (United States)

Gorbunov, P. A.; Vorobyov, S. V.

2017-10-01

In the paper the features of reservoir pressures changes in the northern part of West Siberian oil-and gas province are described. This research is based on the results of hydrodynamic studies in prospecting and explorating wells in Yamal-Nenets Autonomous District. In the Cenomanian, Albian, Aptian and in the top of Neocomian deposits, according to the research, reservoir pressure is usually equal to hydrostatic pressure. At the bottom of the Neocomian and Jurassic deposits zones with abnormally high reservoir pressures (AHRP) are distinguished within Gydan and Yamal Peninsula and in the Nadym-Pur-Taz interfluve. Authors performed the unique zoning of the territory of the Yamal-Nenets Autonomous District according to the patterns of changes of reservoir pressures in the section of the sedimentary cover. The performed zoning and structural modeling allow authors to create a set of the initial reservoir pressures maps for the main oil and gas bearing complexes of the northern part of West Siberia. The results of the survey should improve the efficiency of exploration drilling by preventing complications and accidents during this operation in zones with abnormally high reservoir pressures. In addition, the results of the study can be used to estimate gas resources within prospective areas of Yamal-Nenets Autonomous District.

The Solar Reflectance Index as a Tool to Forecast the Heat Released to the Urban Environment: Potentiality and Assessment Issues

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Alberto Muscio

2018-02-01

Full Text Available Overheating of buildings and urban areas is a more and more severe issue in view of global warming combined with increasing urbanization. The thermal behavior of urban surfaces in the hot seasons is the result of a complex balance of construction and environmental parameters such as insulation level, thermal mass, shielding, and solar reflective capability on one side, and ambient conditions on the other side. Regulations makers and the construction industry have favored the use of parameters that allow the forecasting of the interaction between different material properties without the need for complex analyses. Among these, the solar reflectance index (SRI takes into account solar reflectance and thermal emittance to predict the thermal behavior of a surface subjected to solar radiation through a physically rigorous mathematical procedure that considers assigned air and sky temperatures, peak solar irradiance, and wind velocity. The correlation of SRI with the heat released to the urban environment is analyzed in this paper, as well as the sensitivity of its calculation procedure to variation of the input parameters, as possibly induced by the measurement methods used or by the material ageing.

First report of the successful operation of a side stream supersaturation hypolimnetic oxygenation system in a eutrophic, shallow reservoir.

Science.gov (United States)

Gerling, Alexandra B; Browne, Richard G; Gantzer, Paul A; Mobley, Mark H; Little, John C; Carey, Cayelan C

2014-12-15

Controlling hypolimnetic hypoxia is a key goal of water quality management. Hypoxic conditions can trigger the release of reduced metals and nutrients from lake sediments, resulting in taste and odor problems as well as nuisance algal blooms. In deep lakes and reservoirs, hypolimnetic oxygenation has emerged as a viable solution for combating hypoxia. In shallow lakes, however, it is difficult to add oxygen into the hypolimnion efficiently, and a poorly designed hypolimnetic oxygenation system could potentially result in higher turbidity, weakened thermal stratification, and warming of the sediments. As a result, little is known about the viability of hypolimnetic oxygenation in shallow bodies of water. Here, we present the results from recent successful tests of side stream supersaturation (SSS), a type of hypolimnetic oxygenation system, in a shallow reservoir and compare it to previous side stream deployments. We investigated the sensitivity of Falling Creek Reservoir, a shallow (Zmax = 9.3 m) drinking water reservoir located in Vinton, Virginia, USA, to SSS operation. We found that the SSS system increased hypolimnetic dissolved oxygen concentrations at a rate of ∼1 mg/L/week without weakening stratification or warming the sediments. Moreover, the SSS system suppressed the release of reduced iron and manganese, and likely phosphorus, from the sediments. In summary, SSS systems hold great promise for controlling hypolimnetic oxygen conditions in shallow lakes and reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

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Jui-Yi Ho

2015-04-01

Full Text Available The dynamic relationship between watershed characteristics and rainfall-runoff has been widely studied in recent decades. Since watershed rainfall-runoff is a non-stationary process, most deterministic flood forecasting approaches are ineffective without the assistance of adaptive algorithms. The purpose of this paper is to propose an effective flow forecasting system that integrates a rainfall forecasting model, watershed runoff model, and real-time updating algorithm. This study adopted a grey rainfall forecasting technique, based on existing hourly rainfall data. A geomorphology-based runoff model can be used for simulating impacts of the changing geo-climatic conditions on the hydrologic response of unsteady and non-linear watershed system, and flow updating algorithm were combined to estimate watershed runoff according to measured flow data. The proposed flood forecasting system was applied to three watersheds; one in the United States and two in Northern Taiwan. Four sets of rainfall-runoff simulations were performed to test the accuracy of the proposed flow forecasting technique. The results indicated that the forecast and observed hydrographs are in good agreement for all three watersheds. The proposed flow forecasting system could assist authorities in minimizing loss of life and property during flood events.

A New Method for Fracturing Wells Reservoir Evaluation in Fractured Gas Reservoir

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Jianchun Guo

2014-01-01

Full Text Available Natural fracture is a geological phenomenon widely distributed in tight formation, and fractured gas reservoir stimulation effect mainly depends on the communication of natural fractures. Therefore it is necessary to carry out the evaluation of this reservoir and to find out the optimal natural fractures development wells. By analyzing the interactions and nonlinear relationships of the parameters, it establishes three-level index system of reservoir evaluation and proposes a new method for gas well reservoir evaluation model in fractured gas reservoir on the basis of fuzzy logic theory and multilevel gray correlation. For this method, the Gaussian membership functions to quantify the degree of every factor in the decision-making system and the multilevel gray relation to determine the weight of each parameter on stimulation effect. Finally through fuzzy arithmetic operator between multilevel weights and fuzzy evaluation matrix, score, rank, the reservoir quality, and predicted production will be gotten. Result of this new method shows that the evaluation of the production coincidence rate reaches 80%, which provides a new way for fractured gas reservoir evaluation.

Considering heterogeneities by transmissibilities averaging on adapted meshes in reservoir simulation; Prise en compte des heterogeneites par prise de moyenne des transmissivites sur maillages adaptes en simulation de reservoir